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Professor John Illingworth


Emeritus Professor
BSc, DPhil(Oxon), FIET, DFBMVA

Academic and research departments

Department of Electrical and Electronic Engineering.

Biography

My publications

Publications

Guillemaut J-Y, Drbohlav O, Illingworth J, Sara R (2008) A maximum likelihood surface normal estimation algorithm for Helmholtz stereopsis, VISAPP 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2 pp. 352-359 INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION
Sun W, Hilton A, Smith R, Illingworth J (1999) Building layered animation models from captured data, COMPUTER ANIMATION AND SIMULATION'99 pp. 145-154 SPRINGER-VERLAG WIEN
KITTLER J, ILLINGWORTH J (1985) ON THRESHOLD SELECTION USING CLUSTERING CRITERIA, IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 15 (5) pp. 652-655 IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
PALER K, FOGLEIN J, ILLINGWORTH J, KITTLER J (1984) LOCAL ORDERED GREY LEVELS AS AN AID TO CORNER DETECTION, PATTERN RECOGNITION 17 (5) pp. 535-543 PERGAMON-ELSEVIER SCIENCE LTD
Gilbert A, Illingworth J, Bowden R (2008) Scale Invariant Action Recognition Using Compound Features Mined from Dense Spatio-temporal Corners, Lecture Notes in Computer Science: Proceedings of 10th European Conference on Computer Vision (Part 1) 5302 pp. 222-233 Springer
The use of sparse invariant features to recognise classes of actions or objects has become common in the literature. However, features are often ?engineered? to be both sparse and invariant to transformation and it is assumed that they provide the greatest discriminative information. To tackle activity recognition, we propose learning compound features that are assembled from simple 2D corners in both space and time. Each corner is encoded in relation to its neighbours and from an over complete set (in excess of 1 million possible features), compound features are extracted using data mining. The final classifier, consisting of sets of compound features, can then be applied to recognise and localise an activity in real-time while providing superior performance to other state-of-the-art approaches (including those based upon sparse feature detectors). Furthermore, the approach requires only weak supervision in the form of class labels for each training sequence. No ground truth position or temporal alignment is required during training.
Sanfeliu A, Andrade-Cetto J, Barbosa M, Bowden R, Capitan J, Corominas A, Gilbert A, Illingworth J, Merino L, Mirats JM, Moreno P, Ollero A, Sequeira J, Spaan MTJ (2010) Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas, SENSORS 10 (3) pp. 2274-2314 MDPI AG
STODDART AJ, ILLINGWORTH J, WINDEATT T (1995) OPTIMAL PARAMETER SELECTION FOR DERIVATIVE ESTIMATION FROM RANGE IMAGES, IMAGE AND VISION COMPUTING 13 (8) pp. 629-635 BUTTERWORTH-HEINEMANN LTD
Crida RC, Stoddart AJ, Illingworth J (1997) Using PCA to model shape for process control, INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN 3-D DIGITAL IMAGING AND MODELING, PROCEEDINGS pp. 318-325 I E E E, COMPUTER SOC PRESS
Oshin OT, Gilbert A, Illingworth J, Bowden R (2009) Learning to recognise spatio-temporal interest points, pp. 14-30
In this chapter, we present a generic classifier for detecting spatio-temporal interest points within video, the premise being that, given an interest point detector, we can learn a classifier that duplicates its functionality and which is both accurate and computationally efficient. This means that interest point detection can be achieved independent of the complexity of the original interest point formulation. We extend the naive Bayesian classifier of Randomised Ferns to the spatio-temporal domain and learn classifiers that duplicate the functionality of common spatio-temporal interest point detectors. Results demonstrate accurate reproduction of results with a classifier that can be applied exhaustively to video at frame-rate, without optimisation, in a scanning window approach. © 2010, IGI Global.
ALTHOFF M, BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, SIEBKE H, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, KUCK H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, YEKUTIELI G, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, MCCARDLE J, SEDGEBEER JK, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HEYLAND D, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, FREEMAN J, LECOMTE P, MEYER T, RUDOLPH G, VENKATARAMANIA H, WICKLUND E, WU SL, ZOBERNIG G (1983) CHARGED HADRON COMPOSITION OF THE FINAL-STATE IN E+E- ANNIHILATION AT HIGH-ENERGIES, ZEITSCHRIFT FUR PHYSIK C-PARTICLES AND FIELDS 17 (1) pp. 5-15 SPRINGER VERLAG
PALER K, SMITH A, ALSFORD J, ILLINGWORTH J, KITTLER J, LEWIS J, ADAWAY WGL, BOWDEN PA, THOMAS WV (1984) AUTOMATIC PACKAGING OF INTEGRATED-CIRCUITS, PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS 449 pp. 616-621 SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Hilton A, Beresford D, Gentils T, Smith R, Sun W, Illingworth J (2000) Whole-body modelling of people from multiview images to populate virtual worlds, VISUAL COMPUTER 16 (7) pp. 411-436 SPRINGER
Artolazabal JAR, Illingworth J, Aguado AS (2006) LIGHT: Local invariant generalized Hough Transform, 18th International Conference on Pattern Recognition, Vol 3, Proceedings pp. 304-307 IEEE COMPUTER SOC
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, LOHR B, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHRMANN E, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, FOHRMANN R, KRASEMANN HL, LEU P, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, STERN RA, YARKER S, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, FREEMAN J, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) SCALE BREAKING IN INCLUSIVE CHARGED-PARTICLE PRODUCTION BY E+E- ANNIHILATION, PHYSICS LETTERS B 114 (1) pp. 65-70 ELSEVIER SCIENCE BV
Tena JR, Smith RS, Hamouz A, Kittler J, Hilton A, Illingworth J (2007) 2D face pose normalisation using a 3D morphable model, 2007 IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE pp. 51-56 IEEE
PRINCEN J, ILLINGWORTH J, KITTLER J (1990) A HIERARCHICAL APPROACH TO LINE EXTRACTION BASED ON THE HOUGH TRANSFORM, COMPUTER VISION GRAPHICS AND IMAGE PROCESSING 52 (1) pp. 57-77 ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS
Guillemaut J-Y, Illingworth J (2008) The normalised image of the absolute conic and its application for zooming camera calibration, PATTERN RECOGNITION 41 (12) pp. 3624-3635 PERGAMON-ELSEVIER SCIENCE LTD
Guillemaut JY, Aguado AS, Illingworth J (2005) Using points at infinity for parameter decoupling in camera calibration, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 27 (2) pp. 265-270 IEEE COMPUTER SOC
Brandelik R, Braunschweig W, Gather K, Kadansky V, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Koepke L, Kolanoski H, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Binnie DM, Dornan PJ, Downie MA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Stern RA, Yarker S, Youngman C, Barlow RJ, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Roe B, Salmon GL, Wyatt TR, Bell KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Wu SL, Zobernig G (1980) Evidence for a spin-1 gluon in three-jet events, Physics Letters B 97 (3-4) pp. 453-458
High-energy e+e--annihilation events obtained in the TASSO detector at PETRA have been used to determine the spin of the gluon in the reaction e+e- ’ qqg. We analysed angular correlations between the three jet axes. While vector gluons are consistent with the data (55% confidence limit), scalar gluons are disfavoured by 3.8 standard deviations, corresponding to a confidence level of about 10-4. Our conclusion is free of possible biases due to uncertainties in the fragmentation process or in determining the qqg kinematics from the observed hadrons. © 1980.
Hamouz M, Tena JR, Kittler J, Hilton A, Illingworth J (2007) 3D assisted face recognition: A survey, 3D IMAGING FOR SAFETY AND SECURITY 35 pp. 3-23 SPRINGER
Terry AJ, Zaman M, Illingworth J (2012) Sensor fusion by a novel algorithm for time delay estimation, DIGITAL SIGNAL PROCESSING 22 (3) pp. 439-452 ACADEMIC PRESS INC ELSEVIER SCIENCE
ELMS AJ, ILLINGWORTH J (1994) COMBINING HMMS FOR THE RECOGNITION OF NOISY PRINTED CHARACTERS, BMVC94 - PROCEEDINGS OF THE 5TH BRITISH MACHINE VISION CONFERENCE, VOLS 1 AND 2 pp. 185-194 BRITISH MACHINE VISION CONF
Gilbert A, Illingworth J, Bowden R, Capitan J, Merino L (2009) Accurate fusion of robot, camera and wireless sensors for surveillance applications, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 pp. 1290-1297
Often within the field of tracking people within only fixed cameras are used. This can mean that when the the illumination of the image changes or object occlusion occurs, the tracking can fail. We propose an approach that uses three simultaneous separate sensors. The fixed surveillance cameras track objects of interest cross camera through incrementally learning relationships between regions on the image. Cameras and laser rangefinder sensors onboard robots also provide an estimate of the person. Moreover, the signal strength of mobile devices carried by the person can be used to estimate his position. The estimate from all these sources are then combined using data fusion to provide an increase in performance. We present results of the fixed camera based tracking operating in real time on a large outdoor environment of over 20 non-overlapping cameras. Moreover, the tracking algorithms for robots and wireless nodes are described. A decentralized data fusion algorithm for combining all these information is presented. ©2009 IEEE.
HILTON A, ILLINGWORTH J, WINDEATT T (1995) STATISTICS OF SURFACE CURVATURE ESTIMATES, PATTERN RECOGNITION 28 (8) pp. 1201-1221 PERGAMON-ELSEVIER SCIENCE LTD
PRINCEN J, ILLINGWORTH J, KITTLER J (1994) HYPOTHESIS-TESTING - A FRAMEWORK FOR ANALYZING AND OPTIMIZING HOUGH TRANSFORM PERFORMANCE, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 16 (4) pp. 329-341 IEEE COMPUTER SOC
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Shapira A, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Krasemann HL, Poelz G, Römer O, Schmüser P, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, Pandoulas D, Sedgebeer JK, Stern RA, Yarker S, Bowler MG, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Thomas J, Wyatt TR, Youngman C, Bell KW, Foster B, Hart JC, Proudfoot J, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Barklow T, Freeman J, Meyer T, Rudolph G, Wicklund E, Wu SL, Zobernig G (1982) Exclusive proton-antiproton production in two-photon collisions, Physics Letters B 108 (1) pp. 67-70
Production of proton-antiproton pairs by two-photon scattering has been observed at the electron-position storage ring PETRA. A total of eight proton-antiproton pairs have been identified using the time-of-flight technique. We have measured a total cross section of 4.5 ± 0.8 nb in the photon-photon c.m. energy range 2.0-2.6 GeV. © 1982.
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Mättig P, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Yarker S, Youngman C, Barlow RJ, Brock I, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Roe B, Salmon GL, Wyatt T, Bell KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Wu SL, Zobernig G (1980) Production and properties of the Ä-lepton in e+e- annihilation at C.M. energies from 12 to 31.6 GeV, Physics Letters B 92 (1-2) pp. 199-205
We have observed Ä production in e+e- annihilation at centre-of-mass energies between 12 and 31.6 GeV with cross sections in agreement with the QED Ä-pair cross section. Branching ratios for Ä decay have been measured and are consistent with the world averages. We have determined the cutoff parameters of QED ›+ (›-) to be > 73 GeV (82 GeV) and have obtained an upper limit on the Ä lifetime of 1.4 × 10-12 s(95% CL). © 1980.
Althoff M, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Siebke H, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Franzke J, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Löhr B, Lüke D, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Schütte W, Söding P, Wolf G, Yekutieli G, Dittmar M, Fohrmann R, Krasemann HL, Leu P, Lohrmann E, Pandoulas D, Poelz G, Römer O, Schmüser P, Wiik BH, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, McCardle J, Sedgebeer JK, Bell KW, Bowler MG, Brock IC, Cashmore RJ, Carnegie R, Clarke PEL, Devenish R, Grossmann P, Illingworth J, Salmon GL, Thomas J, Wyatt TR, Youngman C, Foster B, Hart JC, Harvey J, Proudfoot J, Saxon DH, Woodworth PL, Heyland D, Holder M, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Shapira A, Barklow T, Meyer T, Rudolph G, Venkataramania H, Wicklund E, Wu SL (1982) Angular correlations in ³³’Á0Á0 near threshold, Zeitschrift für Physik C Particles and Fields 16 (1) pp. 13-25
We present an analysis of Á0Á0 production by two photons in the Á0Á0 invariant mass range from 1.2 to 2.0 GeV. From a study of the angular correlations in the process ³³’Á0Á0’À- À+À- we exclude a dominant contribution from JP=0- or 2- states. The data indicate sizeable contributions from JP=0+ for four pion masses M4À1.7 GeV. The data are also well described by a model with isotropic production and uncorrelated isotropic decay of the Á0,s. The cross section stays high below the nominal Á0Á0 threshold, i.e. M4À
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Krasemann HL, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer JK, Stern RA, Yarker S, Bowler MG, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Thomas J, Wyatt TR, Youngman C, Bell KW, Foster B, Hart JC, Proudfoot J, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Shapira A, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Lan Wu S, Zobernig G (1981) ›, › production in e+e- annihilation at 33 GeV centre of mass energy, Physics Letters B 105 (1) pp. 75-80
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Shapira A, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Krasemann HL, Poelz G, Römer O, Schmüser P, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer JK, Stern RA, Yarker S, Bowler MG, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Thomas J, Wyatt TR, Youngman C, Bell KW, Foster B, Hart JC, Proudfoot J, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Barklow T, Freeman J, Meyer T, Rudolph G, Wicklund E, Wu SL, Zobernig G (1982) À0 production by e+e- annihilation at 14 and 34 GeV c.m. energy, Physics Letters B 108 (1) pp. 71-76
The process e+e-’ À0 + anything has been measured at c.m. energies of 14 and 34 GeV for À0 energies between 0.5 and 4 GeV. The ratio of À0 to À± production for À momenta between 0.5 and 1.5 GeV/c is measured to be 2Ã(À0)/ [Ã(À+) + Ã(À-)] = 1.3 ± 0.4 (1.2 ± 0.4) at 14 (34) GeV. The scaled cross section (s/¼)dÃ/dx when compared with lower energy (4.9-7.4 GeV) À0 data indicates a substantial scaling violation. © 1982.
Kittler J, Christmas W, de Campos T, Windridge D, Yan F, Illingworth J, Osman M (2013) Domain Anomaly Detection in Machine Perception: A System Architecture and Taxonomy., IEEE Trans Pattern Anal Mach Intell
We address the problem of anomaly detection in machine perception. The concept of domain anomaly is introduced as distinct from the conventional notion of anomaly used in the literature. We propose a unified framework for anomaly detection which exposes the multifaceted nature of anomalies and suggest effective mechanisms for identifying and distinguishing each facet as instruments for domain anomaly detection. The framework draws on the Bayesian probabilistic reasoning apparatus which clearly defines concepts such as outlier, noise, distribution drift, novelty detection (object, object primitive), rare events, and unexpected events. Based on these concepts we provide a taxonomy of domain anomaly events. One of the mechanisms helping to pinpoint the nature of anomaly is based on detecting incongruence between contextual and noncontextual sensor(y) data interpretation. The proposed methodology has wide applicability. It underpins in a unified way the anomaly detection applications found in the literature. To illustrate some of its distinguishing features, in here the domain anomaly detection methodology is applied to the problem of anomaly detection for a video annotation system.
Illingworth J, Jones G, Kittler J, Petrou M, Princen J (1994) Robust statistical methods of 2D and 3D image description, Annals of Mathematics and Artificial Intelligence 10 (1-2) pp. 125-148
In this paper the problem of image feature extraction is considered with emphasis on developing methods which are resilient in the presence of data contamination. The issue of robustness of estimation procedures has received considerable attention in the statistics community [1-3] but its results are only recently being applied to specific image analysis tasks [4-7]. In this paper we show how the design of robust methods applies to image description tasks posed within a statistical hypothesis testing and parameter estimation framework. The methodology is illustrated by applying it to finding robust, optimal estimation kernels for line detection and edge detection. We then discuss the relationship of these optimal solutions to both the well established Hough Transform technique and the standard estimation kernels developed in the statistics literature. The application of standard robust kernels to image analysis tasks is illustrated by two examples which involve circular arc detection in gray-level imagery and planar surface segmentation in depth data. Robust methods are found to be effective general tools for generating 2D and 3D image descriptions. © 1994 J.C. Baltzer AG, Science Publishers.
Yuen P, Mokhtarian F, Khalili N, Illingworth J (2000) Curvature and torsion feature extraction from freeform 3-D meshes at multiple scales, IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 147 (5) pp. 454-462 INST ENGINEERING TECHNOLOGY-IET
Brandelik R, Braunschweig W, Gather K, Kadansky V, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Koepke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Notz D, Pyrlik J, Riethmüller R, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Binnie DM, Dornan PJ, Downie MA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Stern RA, Yarker S, Youngman C, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Wyatt TR, Bell KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Shapira A, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Lan Wu S, Zobernig G (1981) Search for new sequential leptons in e+e- annihilation at petra energies, Physics Letters B 99 (2) pp. 163-168
Brandelik R, Braunschweig W, Gather K, Jaax B, Kadansky V, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Korbach W, Löhr B, Roth F, Rühmer W, Wedemeyer R, Wermes N, Wollstadt M, Bühring R, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Poelz G, Ringel J, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Youngman C, Barlow RJ, Cashmore RJ, Illingworth J, Ogg M, Salmon GL, Bell KW, Chinowsky W, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Kogan E, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Wu SL, Zobernig G (1979) Properties of hadron final states in e+e- annihilation at 13 GeV and 17 GeV center of mass energies, Physics Letters B 83 (2) pp. 261-266
We have observed e+e- hadrons at C.M. energies of 13 GeV and 17 GeV at PETRA using the TASSO detector. We find R(13 GeV) = 5.6 ± 0.7 and R(17 GeV) = 4.0 ± 0.7. The additional systematic uncertainty is 20%. Comparing inclusive charged hadron spectra we observe scaling between 5 GeV and 17 GeV for x = p/pbeam > 0.2; however the 13 GeV cross section is above the 17 GeV cross section for smaller x. This may be due to copious bb? production. The events become increasingly jet like at high energies as evidenced by a shrinking sphericity distribution with increasing energy. © 1979.
KITTLER J, ILLINGWORTH J, PALER K (1983) THE MAGNITUDE ACCURACY OF THE TEMPLATE EDGE DETECTOR, PATTERN RECOGNITION 16 (6) pp. 607-613 PERGAMON-ELSEVIER SCIENCE LTD
ELMS AJ, ILLINGWORTH J (1995) COMBINATION OF HMMS FOR THE REPRESENTATION OF PRINTED CHARACTERS IN NOISY DOCUMENT IMAGES, IMAGE AND VISION COMPUTING 13 (5) pp. 385-392 BUTTERWORTH-HEINEMANN LTD
ALTHOFF M, BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, SIEBKE H, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, KUCK H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HOCHMAN D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, YEKUTIELI G, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, FOSTER B, GARBUTT DA, JONES TD, JONES WG, MCCARDLE J, SEDGEBEER JK, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, LLOYD SL, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HEYLAND D, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, CHERNEY M, MEYER T, RUDOLPH G, VENKATARAMANIA H, WICKLUND E, WU SL, ZOBERNIG G (1983) PRODUCTION OF KK-BAR-PAIRS IN PHOTON PHOTON COLLISIONS AND THE EXCITATION OF THE TENSOR MESON F'(1515), PHYSICS LETTERS B 121 (2-3) pp. 216-222 ELSEVIER SCIENCE BV
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Shapira A, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Krasemann HL, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer JK, Stern RA, Yarker S, Bowler MG, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Thomas J, Wyatt TR, Youngman C, Bell KW, Foster B, Hart JC, Proudfoot J, Saxon DH, Woodwarth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Sau LW, Zobernig G (1981) High pT hadron production in photon-photon collisions, Physics Letters B 107 (4) pp. 290-296
We have studied the properties of hadron production in photon-photon scattering with tagged photons at the e+e- storage ring PETRA. A tail in the pT distribution of particles consistent with pT-4 has been observed. We show that this tail cannot be due to the hadronic part of the photon. Selected events with high pT particles are found to be consistent with a two-jet structure as expected from a point-like coupling of the photons to quarks. The lowest-order cross section predicted for ³³ ’ qq, à = 3 £ eq4 · ó³ ’ ¼¼, is approached from above by the data at large transverse momenta. © 1981.
Oshin O, Gilbert A, Illingworth J, Bowden R (2009) Action recognition using randomised ferns, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 pp. 530-537
This paper presents a generic method for recognising and localising human actions in video based solely on the distribution of interest points. The use of local interest points has shown promising results in both object and action recognition. While previous methods classify actions based on the appearance and/or motion of these points, we hypothesise that the distribution of interest points alone contains the majority of the discriminatory information. Motivated by its recent success in rapidly detecting 2D interest points, the semi-naive Bayesian classification method of Randomised Ferns is employed. Given a set of interest points within the boundaries of an action, the generic classifier learns the spatial and temporal distributions of those interest points. This is done efficiently by comparing sums of responses of interest points detected within randomly positioned spatio-temporal blocks within the action boundaries. We present results on the largest and most popular human action dataset [20] using a number of interest point detectors, and demostrate that the distribution of interest points alone can perform as well as approaches that rely upon the appearance of the interest points. ©2009 IEEE.
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mess KH, Notz D, Pyrlik J, Quarrie DR, Riethmüller R, Shapira A, Söding P, Wolf G, Fohrmann R, Holder M, Krasemann HL, Leu P, Pandoulas D, Poelz G, Römer O, Schmüser P, Wiik BH, Al-Agil I, Beuselinck R, Binnie DM, Campbell AJ, Dornan PJ, Garbutt DA, Jones TD, Jones WG, Lloyd SL, Sedgbeer JK, Stern RA, Yarker S, Bell KW, Bowler MG, Brock IC, Cashmore RJ, Carnegie R, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Thomas J, Wyatt TR, Youngman C, Foster B, Hart JC, Harvey J, Proudfoot J, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Barklow T, Freeman J, Meyer T, Rudolph G, Wicklund E, Wu SL, Zobernig G (1982) Charge asymmetry and weak interaction effects in e+e-’¼+¼- and e+e-’Ä+Ä-, Physics Letters B 110 (2) pp. 173-180
We have measured, at an average centre-of-mass energy of 34.22 GeV a forward-backward charge asymmetry in the reaction e+e-’¼+¼- of value -0.161 ± 0.032. This demonstrates the existence of an axial vector neutral current with coupling strength of geag¼a=0.53 ± 0.10. We have also obtained a limit on the vector coupling strength of gevg¼v
ILLINGWORTH J (1994) SPECIAL ISSUE - BRITISH MACHINE VISION CONFERENCE 1993, IMAGE AND VISION COMPUTING 12 (3) pp. 130-130 ELSEVIER SCIENCE BV
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, VONDRATZIG AS, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, LEU P, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SODING P, WIIK BH, WOLF G, FOHRMANN R, HOLDER M, KRASEMANN HL, POELZ G, ROMER O, RUSCH R, SCHMUSER P, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, PANDOULAS D, SEDGBEER JK, STERN RA, YARKER S, BOWLER MG, BROCK IC, CASHMORE RJ, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, BELL KW, FOSTER B, HART JC, PROUDFOOT J, SAXON DH, WOODWORTH PL, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, FREEMAN J, LECOMTE P, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1981) LAMBDA,LAMBDABAR PRODUCTION IN E+E- ANNIHILATION AT 33 GEV CENTER OF MASS-ENERGY, PHYSICS LETTERS B 105 (1) pp. 75-80 ELSEVIER SCIENCE BV
STODDART AJ, ILLINGWORTH J, WINDEATT T (1994) OPTIMAL PARAMETER SELECTION FOR DERIVATIVE ESTIMATION FROM RANGE IMAGES, BMVC94 - PROCEEDINGS OF THE 5TH BRITISH MACHINE VISION CONFERENCE, VOLS 1 AND 2 pp. 165-174 BRITISH MACHINE VISION CONF
Procter S, Elms AJ, Illingworth J (1998) A method for connected hand-printed numeral recognition using hidden Markov models, IEE Colloquium (Digest) (440)
A method for the recognition of hand-printed numerals using hidden Markov models is described. The method involves the representation of 2D images of a character with two 1D models, one for the pixel columns of the image and the other for the rows. Various normalisations are applied to both the training and test data to reduce variations between characters within a class, resulting in a corresponding improvement in classification performance. In our latest experiments, a character recognition rate of over 93% was achieved on digit strings of variable length.
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, LOHR B, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, FOHRMANN R, KRASEMANN HL, LEU P, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, STERN RA, YARKER S, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, FREEMAN J, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) A MEASUREMENT OF SIGMA-TOT (E+E--]HADRONS) FOR CM ENERGIES BETWEEN 12.0 AND 36.7-GEV, PHYSICS LETTERS B 113 (6) pp. 499-508 ELSEVIER SCIENCE BV
Princen J, Illingworth J, Kittler J (1990) Hypothesis testing: A framework for analysing and optimising Hough transform performance, IEEE Transactions on Pattern Analysis and Machine Intelligence pp. 427-434
Gilbert A, Illingworth J, Bowden R (2010) Action Recognition Using Mined Hierarchical Compound Features, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 33 (5) pp. 883-897 IEEE COMPUTER SOC
Ruiz MC, Illingworth J (2012) Expression classification of 3D faces using local deformations, IET Conference Publications 2012 (600 CP)
One of the most important challenges for face recognition algorithms is dealing with large variability due to facial expression. This paper presents an approach for the expression classification of 3D face scans. The proposed method is based on modelling local deformations which are calculated as the surface change between a neutral face and a face with expression. These deformations are used to train a multiclass/multi-feature LDA classifier. On an unseen face local deformations are calculated automatically using a face with neutral expression as a reference. It is shown that the results obtained are comparable with other similar approaches with the advantage that there is not manual intervention is required for the classification process.
Merino L, Gilbert A, Bowden R, Illingworth J, Capitán J, Ollero A, Ollero A (2012) Data fusion in ubiquitous networked robot systems for urban services, Annales des Telecommunications/Annals of Telecommunications pp. 1-21
There is a clear trend in the use of robots to accomplish services that can help humans. In this paper, robots acting in urban environments are considered for the task of person guiding. Nowadays, it is common to have ubiquitous sensors integrated within the buildings, such as camera networks, and wireless communications like 3G or WiFi. Such infrastructure can be directly used by robotic platforms. The paper shows how combining the information from the robots and the sensors allows tracking failures to be overcome, by being more robust under occlusion, clutter, and lighting changes. The paper describes the algorithms for tracking with a set of fixed surveillance cameras and the algorithms for position tracking using the signal strength received by a wireless sensor network (WSN). Moreover, an algorithm to obtain estimations on the positions of people from cameras on board robots is described. The estimate from all these sources are then combined using a decentralized data fusion algorithm to provide an increase in performance. This scheme is scalable and can handle communication latencies and failures. We present results of the system operating in real time on a large outdoor environment, including 22 nonoverlapping cameras, WSN, and several robots. © 2012 Institut Mines-Télécom and Springer-Verlag.
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) ELECTROWEAK COUPLING-CONSTANTS IN THE LEPTONIC REACTIONS E+E--]E+E- AND E+E--]MU+MU- AND SEARCH FOR SCALAR LEPTONS, PHYSICS LETTERS B 117 (5) pp. 365-371 ELSEVIER SCIENCE BV
Jin Y, Mokhtarian F, Bober M, Illingworth J (2008) Fuzzy chamfer distance and its probabilistic formulation for visual tracking, 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
The paper presents a fuzzy chamfer distance and its probabilistic formulation for edge-based visual tracking. First, connections of the chamfer distance and the Hausdorff distance with fuzzy objective functions for clustering are shown using a reformulation theorem. A fuzzy chamfer distance (FCD) based on fuzzy objective functions and a probabilistic formulation of the fuzzy chamfer distance (PFCD) based on data association methods are then presented for tracking, which can all be regarded as reformulated fuzzy objective functions and minimized with iterative algorithms. Results on challenging sequences demonstrate the performance of the proposed tracking method. ©2008 IEEE.
YUEN HK, ILLINGWORTH J, KITTLER J (1989) DETECTING PARTIALLY OCCLUDED ELLIPSES USING THE HOUGH TRANSFORM, IMAGE AND VISION COMPUTING 7 (1) pp. 31-37 ELSEVIER SCIENCE BV
Brandelik R, Braunschweig W, Gather K, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Köpke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cassel DG, Cooper S, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Notz D, Pyrlik J, Riethmüller R, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Beuselinck R, Binnie DM, Dornan PJ, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Stern RA, Yarker S, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Wyatt TR, Youngman C, Beli KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Shapira A, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Wu SL, Zobernig G (1981) Two-photon excitation of the tensor meson f<sup>0</sup>(1270), Zeitschrift für Physik C Particles and Fields 10 (2) pp. 117-122
We have measured charged particle pair production in two-photon scattering at the e+e- storage ring PETRA. While the main source of such events is the production of lepton pairs, the presence of an additional process is clearly indicated by the measured invariant mass distribution of the two particles and their angular distributions. We determine that the excess is mainly due to the decay f0(1270)’À+À-. We derive a width “(f0’³³)=3.2±0.2±0.6 keV (statistical and systematic). © 1981 Springer-Verlag.
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Mättig P, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Ringel J, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Pevsner A, Sedgbeer J, Yarker S, Youngman C, Barlow RJ, Cashmore RJ, Illingworth J, Ogg M, Roe B, Salmon GL, Bell KW, Chinowsky W, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Sau LW, Zobernig G (1980) Rapid growth of charged particle multiplicity in high energy e+e- annihilations, Physics Letters B 89 (3-4) pp. 418-422
Hadron production by e+e- annihilation has been studied for c.m. energies W between 13 and 31.6 GeV. As a function of 1n W the charged particle multiplicity grows faster at high energy than at lower energies. This is correlated with a rise in the plateau of the rapidity distribution. The cross section sdÃ/dx is found to scale within ±30% for x > 0.2 and 5 d W d 31.6 GeV. © 1980.
Kittler J, Illingworth J, Foglein J, Paler K (1984) AUTOMATIC THRESHOLDING ALGORITHM AND ITS PERFORMANCE., Proceedings - International Conference on Pattern Recognition pp. 287-289
A novel method of automatic threshold selection based on a simple image statistic is proposed. The method avoids the analysis of complicated image histograms. The properties of the algorithm are presented and experimentally verified on computer generated and real world images.
KITTLER J, ILLINGWORTH J, FOGLEIN J (1985) THRESHOLD SELECTION BASED ON A SIMPLE IMAGE STATISTIC, COMPUTER VISION GRAPHICS AND IMAGE PROCESSING 30 (2) pp. 125-147 ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS
STODDART AJ, HILTON A, ILLINGWORTH J (1994) SLIME - A NEW DEFORMABLE SURFACE, BMVC94 - PROCEEDINGS OF THE 5TH BRITISH MACHINE VISION CONFERENCE, VOLS 1 AND 2 pp. 285-294 BRITISH MACHINE VISION CONF
Kittler J, Illingworth J, Ng I (1990) A new 2D quadrature polar separable filter and its application to texture analysis, Proceedings - IEEE International Symposium on Circuits and Systems 2 pp. 1050-1053
The frequency response of the filter consists of two independent parts. The first is a prolate spheroidal sequence that is dependent on the polar radius. The second is a cosine function of the polar angle. The product of these two parts constitutes a 2-D filtering function. The frequency characteristics of the new filter are similar to that of the 2-D Cartesian separable filter which is defined in terms of two prolate spheroidal sequences. However, in contrast to the 2-D Cartesian separable filter, the position and direction of the new filter in the frequency domain is easy to control. Some applications of the new filter in texture processing, such as generation of synthetic texture, estimation of texture orientation, feature extraction, and texture segmentation, are discussed.
Kittler J, Hamouz M, Tena JR, Hilton A, Illingworth J, Ruiz M (2005) 3D assisted 2D face recognition: Methodology, PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS 3773 pp. 1055-1065 SPRINGER-VERLAG BERLIN
KITTLER J, ILLINGWORTH J (1985) RELAXATION LABELING ALGORITHMS - A REVIEW, IMAGE AND VISION COMPUTING 3 (4) pp. 206-216 ELSEVIER SCIENCE BV
Procter S, Illingworth J (1997) ForeSight: Fast object recognition using geometric hashing with edge-triple features, INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL I pp. 889-892 I E E E, COMPUTER SOC PRESS
Princen J, Illingworth J, Kittler J (1992) A formal definition of the Hough transform: Properties and relationships, Journal of Mathematical Imaging and Vision 1 (2) pp. 153-168
Shape, in both 2D and 3D, provides a primary cue for object recognition and the Hough transform (P.V.C. Hough, U.S. Patent 3,069,654, 1962) is a heuristic procedure that has received considerable attention as a shape-analysis technique. The literature that covers application of the Hough transform is vast; however, there have been few analyses of its behavior. We believe that one of the reasons for this is the lack of a formal mathematical definition. This paper presents a formal definition of the Hough transform that encompasses a wide variety of algorithms that have been suggested in the literature. It is shown that the Hough transform can be represented as the integral of a function that represents the data points with respect to a kernel function that is defined implicitly through the selection of a shape parameterization and a parameter-space quantization. The kernel function has dual interpretations as a template in the feature space and as a point-spread function in the parameter space. A novel and powerful result that defines the relationship between parameterspace quantization and template shapes is provided. A number of interesting implications of the formal definition are discussed. It is shown that the Radon transform is an incomplete formalism for the Hough transform. We also illustrate that the Hough transform has the general form of a generalized maximum-likelihood estimator, although the kernel functions used in estimators tend to be smoother. These observations suggest novel ways of implementing Hough-like algorithms, and the formal definition forms the basis of work for optimizing aspects of Hough transform performance (see J. Princen et. al., Proc. IEEE 3rd Internat. Conf. Comput. Vis., 1990, pp. 427-435). © 1992 Kluwer Academic Publishers.
Brandelik R, Braunschweig W, Gather K, Kadansky V, Kirschfink FJ, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Koepke L, Kolanoski H, Leu P, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Notz D, Pyrlik J, Riethmüller R, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Al-Agil I, Beuselink R, Binnie DM, Dornan PJ, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Stern RA, Yarker S, Brock IC, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Salmon GL, Wyatt TR, Youngman C, Bell KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Mikenberg G, Revel D, Ronat E, Shapira A, Barklow T, Freeman J, Lecomte P, Meyer T, Rudolph G, Wicklund E, Lan Wu S, Zobernig G (1981) Evidence for charged primary partons in e+e- ’ 2 jets, Physics Letters B 100 (4) pp. 357-363
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Mättig P, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Korbach W, Leu P, Löhr B, Roth F, Rühmer W, Wedemeyer R, Wermes N, Wollstadt M, Bühring R, Fohrmann R, Heyland D, Hultschig H, Joos P, Koch W, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, S?oding P, Wiik BH, Wolf G, Holder M, Poelz G, Ringel J, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Pevsner A, Sedgebeer J, Yarker S, Youngman C, Barlow RJ, Cashmore RJ, Illingworth J, Ogg M, Salmon GL, Bell KW, Chinowsky W, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Kogan E, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Sau LW, Zobernig G (1979) Evidence for planar events in e+e- annihilation at high energies, Physics Letters B 86 (2) pp. 243-249
Hadron jets produced in e+e- annihilation between 13 GeV and 31.6 GeV in c.m. at PETRA are analyzed. The transverse momentum of the jets is found to increase strongly with c.m. energy. The broadening of the jets is not uniform in azimuthal angle around the quark direction but tends to yield planar events with large and growing transverse momenta in the plane and smaller transverse momenta normal to the plane. The simple qq collinear jet picture is ruled out. The observation of planar events shows that there are three basic particles in the final state. Indeed, several events with three well-separated jets of hadrons are observed at the highest energies. This occurs naturally when the outgoing quark radiates a hard noncollinear gluon, i.e., e+e- ’ qqg with the quarks and the gluons fragmenting into hadrons with limited transverse momenta. © 1979.
KITTLER J, EGGLETON J, ILLINGWORTH J, PALER K (1987) AN AVERAGING EDGE DETECTOR, PATTERN RECOGNITION LETTERS 6 (1) pp. 27-32 ELSEVIER SCIENCE BV
Tena JR, Hamouz M, Hilton A, Illingworth J (2006) A validated method for dense non-rigid 3D face registration, Proceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006
Deformable surface fitting methods have been widely used to establish dense correspondence across different 3D objects of the same class. Dense correspondence is a critical step in constructing morphable face models for face recognition. In this paper a mainstream method for constructing dense correspondences is evaluated on 912 3D face scans from the Face Recognition Grand Challenge FRGC V1 database. A number of modifications to the standard deformable surface approach are introduced to overcome limitations identified in the evaluation. Proposed modifications include multi-resolution fitting, adaptive correspondence search range and enforcing symmetry constraints. The modified deformable surface approach is validated on the 912 FRGC 3D face scans and is shown to overcome limitations of the standard approach which resulted in gross fitting errors. The modified approach halves the rms fitting error with 98% of points within 0.5mm of their true position compared to 67% with the standard approach. © 2006 IEEE.
Gartshore R, Palmer P, Illingworth J (2005) A novel exploration algorithm based on a improvement strategy, International Journal of Advanced Robotic Systems 2 (4) pp. 287-294
In this paper we present a strategy for the problem of exploring an unknown 2D environment. Existing techniques can be methodical, goal oriented or non-reactive to additional knowledge received at each new viewpoint. We present an approach which is not goal driven, but rather seeks new unseen areas to view and explore. The novelty of the strategy presented is the use of a view-improvement technique along with an optimal viewpoint planning method for the calculation and selection of the next-best-viewpoint. The strategy is designed for a sensor system with a limited field-of-view. Example explorations are presented and we demonstrate that the strategy finds new areas to view without exhaustive searching.
YUEN HK, PRINCEN J, ILLINGWORTH J, KITTLER J (1990) COMPARATIVE-STUDY OF HOUGH TRANSFORM METHODS FOR CIRCLE FINDING, IMAGE AND VISION COMPUTING 8 (1) pp. 71-77 ELSEVIER SCIENCE BV
Li Y, Hilton A, Illingworth J (2002) A relaxation algorithm for real-time multiple view 3D-tracking, IMAGE AND VISION COMPUTING 20 (12) PII S0262-8856(02)00094-X pp. 841-859 ELSEVIER SCIENCE BV
Ng I, Illingworth J, Jones G (1995) Novel method for segmentation of cones and cylinders from geometrically fused depth maps, IEE Conference Publication (410) pp. 544-548
This study proposes a new algorithm for cylinder and conic surface extraction. The algorithm exploits pairs of surfaces patches to generate potential curved surface parameters which are in turn clustered using an un-supervised technique. This algorithm has the desirable property of being able to work parse, as well as dense depth data, and avoids any restrictive assumptions that the data is presented in a 2D image format. It is shown that the proposed algorithm is successful even for quite complicated depth images.
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Mättig P, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolff G, Fohrmann R, Holder M, Poelz G, Ringel J, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Pevsner A, Sedgbeer J, Yarker S, Youngman C, Barlow RJ, Cashmore RJ, Illingworth J, Ogg M, Roe B, Salmon GL, Bell KW, Chinowsky W, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Wu SL, Zobernig G (1980) e<sup>+</sup> e<sup>-</sup> annihilation at high energies and search for the t-quark continuum contribution, Zeitschrift für Physik C Particles and Fields 4 (2) pp. 87-93
Measurements of R, sphericity and thrust are presented for c.m. energies between 12 and 31.6 GeV. A possible contribution of a t {Mathematical expression} continuum can be ruled out for c.m. energies between 16 and 31 GeV. © 1980 Springer-Verlag.
Hilton A, Stoddart AJ, Illingworth J, Windeatt T (1996) Marching triangles: Range image fusion for complex object modelling, INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, PROCEEDINGS - VOL II pp. 381-384 I E E E
Sun W, Hilton A, Smith R, Illingworth J (2001) Layered animation of captured data, VISUAL COMPUTER 17 (8) pp. 457-474 SPRINGER-VERLAG
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, LOHR B, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOEHLER P, KOTZ U, KOWALSKI H, LADAGE A, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SHAPIRA A, SODING P, WOLF G, FOHRMANN R, HOLDER M, KRASEMANN HL, LEU P, PANDOULAS D, POELZ G, ROMER O, RUSCH R, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, STERN RA, YARKER S, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, BARKLOW T, FREEMAN J, LECOMTE P, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) CHARGED PION-PRODUCTION IN E+E- ANNIHILATION AT 14,22 AND 34 GEV CM ENERGY, PHYSICS LETTERS B 113 (1) pp. 98-104 ELSEVIER SCIENCE BV
Elms AJ, Procter S, Illingworth J (1998) The advantage of using an HMM-based approach for faxed word recognition, International Journal on Document Analysis and Recognition 1 (1) pp. 18-36
A method for word recognition based on the use of hidden Markov models (HMMs) is described. An evaluation of its performance is presented using a test set of real printed documents that have been subjected to severe photocopy and fax transmission distortions. A comparison with a commercial OCR package highlights the inherent advantages of a segmentation-free recognition strategy when the word images are severely distorted, as well as the importance of using contextual knowledge. The HMM method makes only one quarter of the number of word errors made by the commercial package when tested on word images taken from faxed pages. © 1998 Springer-Verlag Berlin Heidelberg.
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, von Dratzig AS, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Koepke L, Kolanoski H, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Burkhardt H, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mättig P, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Yarker S, Youngman C, Barlow RJ, Brock I, Cashmore RJ, Devenish R, Grossmann P, Illingworth J, Ogg M, Roe B, Salmon GL, Wyatt T, Bell KW, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Duchovni E, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Wu SL, Zobernig G (1980) RHO-RHO production by two photon scattering, Physics Letters B 97 (3-4) pp. 448-452
Princen J, Yuen HK, Illingworth J, Kittler J (1989) Comparison of Hough Transform methods, IEE Conference Publication (307) pp. 73-77
An important aspect of any scientific discipline is the objective and independent comparison of algorithms which perform common tasks. In image analysis this problem has been neglected. In this paper we present the results and conclusions of a comparison of four Hough Transform, HT, based line finding algorithms on a range of realistic images from the industrial domain. We introduce the line detection problem and show the role of the Hough Transform in it. The basic idea underlying the Hough Transform is presented and is followed by a brief description of each of the four HT based methods considered in our work. The experimental evaluation and comparison of the four methods is given and a section offers our conclusions on the merits and deficiencies of each of the four methods.
Procter S, Illingworth J (1999) Handwriting recognition using HMMs and a conservative level building algorithm, SEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING AND ITS APPLICATIONS (465) pp. 736-739 INST ELECTRICAL ENGINEERS INSPEC INC
Starck J, Collins G, Smith R, Hilton A, Illingworth J (2003) Animate statues, MACHINE VISION AND APPLICATIONS 14 (4) pp. 248-259 SPRINGER
Hobson P, Illingworth J (2004) Special section from VIE 2003, IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 151 (4) pp. 297-297 IEE-INST ELEC ENG
Procter S, Illingworth J, Elms AJ (1998) The recognition of handwritten digit strings of unknown length using hidden Markov models, FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 pp. 1515-1517 IEEE COMPUTER SOC
Guillemaut JY, Drbohlav O, Sara R, Illingworth J (2004) Helmholtz stereopsis on rough and strongly textured surfaces, 2ND INTERNATIONAL SYMPOSIUM ON 3D DATA PROCESSING, VISUALIZATION, AND TRANSMISSION, PROCEEDINGS pp. 10-17 IEEE COMPUTER SOC
HILTON A, STODDART A, ILLINGWORTH J, WINDEATT T (1994) AUTOMATIC INSPECTION OF LOADED PCBS USING 3D RANGE DATA, MACHINE VISION APPLICATIONS IN INDUSTRIAL INSPECTION II 2183 pp. 226-237 SPIE - INT SOC OPTICAL ENGINEERING
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, LOHR B, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SHAPIRA A, SODING P, WOLF G, FOHRMANN R, HOLDER M, KRASEMANN HL, LEU P, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, STERN RA, YARKER S, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, DEVENISH R, GROSSMANN P, ILLINGWORTH J, OGG M, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, BARKLOW T, FREEMAN J, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) CHARGE ASYMMETRY AND WEAK INTERACTION EFFECTS IN EPSILON+ EPSILON- -] MU+ MU- AND EPSILON+ EPSILON- -] TAU+ TAU-, PHYSICS LETTERS B 110 (2) pp. 173-180 ELSEVIER SCIENCE BV
PROCTER S, ILLINGWORTH J (1994) A COMPARISON OF THE RANDOMISED HOUGH TRANSFORM AND A GENETIC ALGORITHM FOR ELLIPSE EXTRACTION, PATTERN RECOGNITION IN PRACTICE IV: MULTIPLE PARADIGMS, COMPARATIVE STUDIES AND HYBRID SYSTEMS 16 pp. 449-460 ELSEVIER SCIENCE PUBL B V
Procter S, Illingworth J (1998) Combining HMM classifiers in a handwritten text recognition system, 1998 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL 2 pp. 934-938 IEEE COMPUTER SOC
Procter S, Illingworth J, Mokhtarian F (2000) Cursive handwriting recognition using hidden Markov models and a lexicon-driven level building algorithm, IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 147 (4) pp. 332-339 IEE-INST ELEC ENG
HILTON A, ILLINGWORTH J, WINDEATT T (1994) STATISTICS OF SURFACE CURVATURE ESTIMATES, PROCEEDINGS OF THE 12TH IAPR INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION - CONFERENCE A: COMPUTER VISION & IMAGE PROCESSING pp. 37-41 I E E E, COMPUTER SOC PRESS
Zaman M, Illingworth J (2004) Interval-based time synchronisation of sensor data in a mobile robot, Proceedings of the 2004 Intelligent Sensors, Sensor Networks & Information Processing Conference pp. 463-468 IEEE
Hoad P, Illingworth J (1995) Automatic control of camera pan, zoom and focus for improving object recognition, IEE Conference Publication (410) pp. 291-295
The detection and recognition of objects from image data is a difficult problem that is closely related to problems of segmentation and stable and reliable feature detection. Feature detection is dependent on a number of factors such as the resolution at which data is sensed. In normal vision systems, the sensor is static with no ability to pan or zoom. However, with the advent of active robot vision heads such as GETAFIX, there is the ability to pan and zoom onto areas of interest. In this article, the use of GETAFIX for object recognition by automatic active panning, zooming and focusing is considered. This is demonstrated by conducting experiments for the case of detecting cylindrical 3D objects in table-top scenes.
Guillemaut JY, Aguado AS, Illingworth J (2003) Calibration of a zooming camera using the Normalized Image of the Absolute Conic, FOURTH INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING, PROCEEDINGS pp. 225-232 IEEE COMPUTER SOC
Hilton A, Stoddart AJ, Illingworth J, Windeatt T (1998) Implicit surface-based geometric fusion, COMPUTER VISION AND IMAGE UNDERSTANDING 69 (3) pp. 273-291 ACADEMIC PRESS INC
Hamouz M, Tena JR, Kittler J, Hilton A, Illingworth J (2006) Algorithms for 3D-assisted face recognition, 2006 IEEE 14TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1 AND 2 pp. 826-829 IEEE
Smith R, Sun W, Hilton A, Illingworth J (2000) Layered animation using displacement maps, COMPUTER ANIMATION 2000, PROCEEDINGS pp. 146-151 IEEE COMPUTER SOC
Illingworth J, Hilton A (1998) Looking to build a model world: Automatic construction of static object models using computer vision, ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL 10 (3) pp. 103-113 IEE-INST ELEC ENG
NG I, KITTLER J, ILLINGWORTH J (1993) SUPERVISED SEGMENTATION USING A MULTIRESOLUTION DATA REPRESENTATION, SIGNAL PROCESSING 31 (2) pp. 133-163 ELSEVIER SCIENCE BV
Hilton A, Illingworth J (1997) Multi-resolution geometric fusion, INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN 3-D DIGITAL IMAGING AND MODELING, PROCEEDINGS pp. 181-188 I E E E, COMPUTER SOC PRESS
Hilton A, Stoddart AJ, Illingworth J, Windeatt T (1996) Reconstruction of 3D Delaunay surface models of complex objects, INFORMATION INTELLIGENCE AND SYSTEMS, VOLS 1-4 pp. 2445-2450 INT ACADEMIC PUBL
BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, SIEBKE H, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HEYLAND D, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, LYNCH HL, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, DITTMAR M, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, SEDGBEER JK, STERN R, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, MEYER T, RUDOLPH G, WICKLUND E, WU SL, ZOBERNIG G (1982) INCLUSIVE-P0 PRODUCTION IN E+E- ANNIHILATION AT HIGH-ENERGY, PHYSICS LETTERS B 117 (1-2) pp. 135-140 ELSEVIER SCIENCE BV
Li Y, Hilton A, Illingworth J (2001) Towards reliable real-time multiview tracking, 2001 IEEE WORKSHOP ON MULTI-OBJECT TRACKING, PROCEEDINGS pp. 43-50 IEEE COMPUTER SOC
ILLINGWORTH J, KITTLER J (1987) THE ADAPTIVE HOUGH TRANSFORM, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 9 (5) pp. 690-698 IEEE COMPUTER SOC
Kittler J, Illingworth J, Foglein J, Paler K (1984) AUTOMATIC THRESHOLDING METHOD FOR WAVEFORM SEGMENTATION., Proceedings of the International Conference on Digital Signal Processing pp. 727-732
REMAGNINO P, ILLINGWORTH J, MATAS J (1995) INTERNATIONAL CONTROL OF CAMERA LOOK DIRECTION AND VIEWPOINT IN AN ACTIVE VISION SYSTEM, IMAGE AND VISION COMPUTING 13 (2) pp. 79-88 BUTTERWORTH-HEINEMANN LTD
YANG DK, ILLINGWORTH J (1994) CALIBRATING A ROBOT CAMERA, BMVC94 - PROCEEDINGS OF THE 5TH BRITISH MACHINE VISION CONFERENCE, VOLS 1 AND 2 pp. 519-528 BRITISH MACHINE VISION CONF
ALTHOFF M, BRANDELIK R, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, SIEBKE H, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, KUCK H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, YEKUTIELI G, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, FOSTER B, GARBUTT DA, JONES TD, JONES WG, MCCARDLE J, SEDGBEER JK, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, LLOYD SL, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HEYLAND D, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, CHERNEY M, MEYER T, RUDOLPH G, VENKATARAMANIA H, WICKLUND E, WU SL, ZOBERNIG G (1983) SEARCH FOR CHARGED HIGGS AND TECHNIPIONS AT PETRA, PHYSICS LETTERS B 122 (1) pp. 95-102 ELSEVIER SCIENCE BV
KITTLER J, ILLINGWORTH J (1986) MINIMUM ERROR THRESHOLDING, PATTERN RECOGNITION 19 (1) pp. 41-47 PERGAMON-ELSEVIER SCIENCE LTD
Smith RS, Kittler J, Hamouz M, Illingworth J (2006) Face recognition using angular LDA and SVM ensembles, 18th International Conference on Pattern Recognition, Vol 3, Proceedings pp. 1008-1012 IEEE COMPUTER SOC
Ruiz MC, Illingworth J (2008) Automatic landmarking of faces in 3D-ALF3D, IET Conference Publications (543 CP) pp. 41-46
We present an algorithm for automatic localization of landmarks on 3D faces. An active shape model, ASM, is used as a statistical joint location model for configurations of facial features. The ASM is adapted to individual faces via a guided search whereby landmark specific shape index models are matched to local surface patches. The algorithm is trained and tested on 912 3D face images from the face recognition grand challenge dataset. Results demonstrate that the automatic procedure successfully and reliably locates landmarks and, compared with an iterative closest point (ICP) algorithm, reduces the mean error for location of landmarks by nearly a half. ©2008 The Institution of Engineering and Technology.
Hilton A, Illingworth J (2000) Geometric fusion for a hand-held 3D sensor, MACHINE VISION AND APPLICATIONS 12 (1) pp. 44-51 SPRINGER
Brandelik R, Braunschweig W, Gather K, Kadansky V, Lübelsmeyer K, Mättig P, Martyn HU, Peise G, Rimkus J, Sander HG, Schmitz D, Schultz von Dratzig A, Trines D, Wallraff W, Boerner H, Fischer HM, Hartmann H, Hilger E, Hillen W, Knop G, Leu P, Löhr B, Wedemeyer R, Wermes N, Wollstadt M, Cassel DG, Heyland D, Hultschig H, Joos P, Koch W, Koehler P, Kötz U, Kowalski H, Ladage A, Lüke D, Lynch HL, Mikenberg G, Notz D, Pyrlik J, Riethmüller R, Schliwa M, Söding P, Wiik BH, Wolf G, Fohrmann R, Holder M, Poelz G, Ringel J, Römer O, Rüsch R, Schmüser P, Binnie DM, Dornan PJ, Downie NA, Garbutt DA, Jones WG, Lloyd SL, Pandoulas D, Sedgbeer J, Yanker S, Youngman C, Barlow RJ, Cashmore RJ, Illingworth J, Ogg M, Roe B, Salmon GL, Bell KW, Chinowsky W, Foster B, Hart JC, Proudfoot J, Quarrie DR, Saxon DH, Woodworth PL, Eisenberg Y, Karshon U, Revel D, Ronat E, Shapira A, Freeman J, Lecomte P, Meyer T, Lan Wu S, Zobernig G (1979) Energy scan for narrow states in e+e- annihilation at C.M. energies between 29.90 and 31.46 GeV, Physics Letters B 88 (1-2) pp. 199-202
A fine energy scan has been performed to search for narrow states in e+e- annihilation at c.m. energies between 29.90 and 31.46 GeV. No such state has been observed. The 90% confidence upper limit on the leptonic decay width times the hadronic decay branching ratio is “eeBh
Artolazabal JAR, Illingworth J (2005) 3DSVHT: Extraction of 3D linear motion via multi-view, temporal evidence accumulation, ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS 3708 pp. 563-570 SPRINGER-VERLAG BERLIN
ALTHOFF M, BRAUNSCHWEIG W, GATHER K, KIRSCHFINK FJ, LUBELSMEYER K, MARTYN HU, PEISE G, RIMKUS J, SANDER HG, SCHMITZ D, SIEBKE H, TRINES D, WALLRAFF W, BOERNER H, FISCHER HM, HARTMANN H, HILGER E, HILLEN W, KNOP G, KOPKE L, KOLANOSKI H, WEDEMEYER R, WERMES N, WOLLSTADT M, BURKHARDT H, COOPER S, FRANZKE J, HULTSCHIG H, JOOS P, KOCH W, KOTZ U, KOWALSKI H, LADAGE A, LOHR B, LUKE D, MATTIG P, MESS KH, NOTZ D, PYRLIK J, QUARRIE DR, RIETHMULLER R, SCHUTTE W, SODING P, WOLF G, YEKUTIELI G, DITTMAR M, FOHRMANN R, KRASEMANN HL, LEU P, LOHRMANN E, PANDOULAS D, POELZ G, ROMER O, SCHMUSER P, WIIK BH, ALAGIL I, BEUSELINCK R, BINNIE DM, CAMPBELL AJ, DORNAN PJ, GARBUTT DA, JONES TD, JONES WG, LLOYD SL, MCCARDLE J, SEDGEBEER JK, BELL KW, BOWLER MG, BROCK IC, CASHMORE RJ, CARNEGIE R, CLARKE PEL, DEVENISH R, GROSSMANN P, ILLINGWORTH J, SALMON GL, THOMAS J, WYATT TR, YOUNGMAN C, FOSTER B, HART JC, HARVEY J, PROUDFOOT J, SAXON DH, WOODWORTH PL, HEYLAND D, HOLDER M, DUCHOVNI E, EISENBERG Y, KARSHON U, MIKENBERG G, REVEL D, RONAT E, SHAPIRA A, BARKLOW T, MEYER T, RUDOLPH G, VENKATARAMANIA H, WICKLUND E, WU SL, ZOBERNIG G (1982) ANGULAR-CORRELATIONS IN GAMMA-GAMMA-]RHO0-RHO0 NEAR THRESHOLD, ZEITSCHRIFT FUR PHYSIK C-PARTICLES AND FIELDS 16 (1) pp. 13-25 SPRINGER VERLAG
ILLINGWORTH J, KITTLER J (1988) A SURVEY OF THE HOUGH TRANSFORM, COMPUTER VISION GRAPHICS AND IMAGE PROCESSING 44 (1) pp. 87-116 ACADEMIC PRESS INC JNL-COMP SUBSCRIPTIONS
Merino L, Gilbert A, Capitán J, Bowden R, Illingworth J, Ollero A (2012) Data fusion in ubiquitous networked robot systems for urban services, Annales des Telecommunications/Annals of Telecommunications 67 (7-8) pp. 355-375 Springer
There is a clear trend in the use of robots to accomplish services that can help humans. In this paper, robots acting in urban environments are considered for the task of person guiding. Nowadays, it is common to have ubiquitous sensors integrated within the buildings, such as camera networks, and wireless communications like 3G or WiFi. Such infrastructure can be directly used by robotic platforms. The paper shows how combining the information from the robots and the sensors allows tracking failures to be overcome, by being more robust under occlusion, clutter, and lighting changes. The paper describes the algorithms for tracking with a set of fixed surveillance cameras and the algorithms for position tracking using the signal strength received by a wireless sensor network (WSN). Moreover, an algorithm to obtain estimations on the positions of people from cameras on board robots is described. The estimate from all these sources are then combined using a decentralized data fusion algorithm to provide an increase in performance. This scheme is scalable and can handle communication latencies and failures. We present results of the system operating in real time on a large outdoor environment, including 22 nonoverlapping cameras,WSN, and several robots. © Institut Mines-Télécom and Springer-Verlag 2012.
Gilbert Andrew, Illingworth John, Bowden Richard (2009) Fast realistic multi-action recognition using mined dense spatio-temporal features, Proceedings of the 12th IEEE International Conference on Computer Vision pp. 925-931 IEEE
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it is not necessarily optimal in terms of class separability and classification. This paper proposes a novel approach that uses very dense corner features that are spatially and temporally grouped in a hierarchical process to produce an overcomplete compound feature set. Frequently reoccurring patterns of features are then found through data mining, designed for use with large data sets. The novel use of the hierarchical classifier allows real time operation while the approach is demonstrated to handle camera motion, scale, human appearance variations, occlusions and background clutter. The performance of classification, outperforms other state-of-the-art action recognition algorithms on the three datasets; KTH, multi-KTH, and Hollywood. Multiple action localisation is performed, though no groundtruth localisation data is required, using only weak supervision of class labels for each training sequence. The Hollywood dataset contain complex realistic actions from movies, the approach outperforms the published accuracy on this dataset and also achieves real time performance. ©2009 IEEE.