Dr Teo de Campos
Research Fellow
Qualifications: DPhil in Engineering Sciences, Oxford, 2006
Email: t.decampos@surrey.ac.uk
Phone: Work: 01483 68 6032
Room no: 7A AB 05
Further information
Biography
I'm currently focusing my efforts on the ACASVA project, supporting several aspects of this project, in particular working with action recognition and transfer learning, with my PhD student Nazli FarajiDavar. I work closely with Bill Christmas, Josef Kittler and others. In the past, I've also collaborated with Mark Barnard and Krystian Mikolajczyk.
Here is a summary of activities in my previous jobs and courses:
- At Xerox, I was the main investigator of a highly collaborative work package (WP) of the PinView project. This WP was about image categorisation using visual attention information. Among other things, this work resulted in a paper published at CVIU. I also supervised Julian McAuley's intership and we worked on image region labelling and graph matching. His internship was outstandingly productive: in just 4 months of work, we submitted two patent applications and two papers for conferences.
- At Microsoft, I worked with Manik Varma on image classification using multiple types of image descriptors and bags-of-visual-words. One of the outcomes of this work was the Chars74K Character Recognition Dataset.
- At Sharp, I worked on image processing methods to enhance the image quality on novel LCD technologies, such as multi-view and stereoscopic (3D) displays. I also worked as a member of the "New Project" Project (yes, the word project appears twice :-)).
- My doctorate in Oxford was about tracking articulated objects in 3D, in real-time. I explored methods of both these approaches: model-based (projective geometry) and discriminative (regression-based). My thesis page gives all the details and shows some demos.
- I've also done a masters at the University of Sao Paulo (in the Creativision group) on the application of feature selection for face recognition. My thesis was awarded the best MSc thesis by the Brazilian Computer Society in a nationwide contest.
Research Interests
- transfer learning
- human action recognition
- image categorisation and retrieval
- visual attention
Further details can be found on my personal web page.
Publications
The reference in this page have been generated automatically. This link may be more accurate and it also contains PDFs for download.
Highlights
- . (2012) 'Modeling the Spatial Layout of Images Beyond Spatial Pyramids'. Pattern Recognition Letters,
- . (2012) 'Images as Sets of Locally Weighted Features'. Elsevier Computer Vision and Image Understanding (CVIU), 116 (1), pp. 68-85.
- . (2011) 'Transductive Transfer Learning for Action Recognition in Tennis Games'. 3rd International Workshop on Video Event Categorization, Tagging and Retrieval for Real-World Applications (VECTaR), in conjunction with ICCV,
- .
(2011) 'An evaluation of bags-of-words and spatio-temporal shapes for action recognition'. 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011, , pp. 344-351.Full text is available at: http://epubs.surrey.ac.uk/74813/
Abstract
Bags-of-visual-Words (BoW) and Spatio-Temporal Shapes (STS) are two very popular approaches for action recognition from video. The former (BoW) is an un-structured global representation of videos which is built using a large set of local features. The latter (STS) uses a single feature located on a region of interest (where the actor is) in the video. Despite the popularity of these methods, no comparison between them has been done. Also, given that BoW and STS differ intrinsically in terms of context inclusion and globality/locality of operation, an appropriate evaluation framework has to be designed carefully. This paper compares these two approaches using four different datasets with varied degree of space-time specificity of the actions and varied relevance of the contextual background. We use the same local feature extraction method and the same classifier for both approaches. Further to BoW and STS, we also evaluated novel variations of BoW constrained in time or space. We observe that the STS approach leads to better results in all datasets whose background is of little relevance to action classification. © 2010 IEEE.
- . (2010) 'Unified graph matching in Euclidean spaces'. San Francisco : IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
- . (2009) 'Hierarchical Image-Region Labeling via Structured Learning'. London : Proceedings of the British Machine Vision Conference,
- . (2009) 'CHARACTER RECOGNITION IN NATURAL IMAGES'. INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, Lisbon, PORTUGAL: 4th International Conference on Computer Vision Theory and Applications, pp. 273-280.
Journal articles
- . (2012) 'Modeling the Spatial Layout of Images Beyond Spatial Pyramids'. Pattern Recognition Letters,
- . (2012) 'Images as Sets of Locally Weighted Features'. Elsevier Computer Vision and Image Understanding (CVIU), 116 (1), pp. 68-85.
- . (2006) 'Regression-based hand pose estimation from multiple cameras'. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, pp. 782-789.
- . (2006) 'Recovering articulated pose: a comparison of two pre and postimposed constraint methods.'. IEEE Trans Pattern Anal Mach Intell, United States: 28 (1), pp. 163-168.
Conference papers
- . (2011) 'Domain Adaptation in the Context of Sport Video Action Recognition'. Sierra Nevada, Spain: NIPS 2011 Domain Adaptation Workshop
- .
(2011) 'Improved Detection of Ball Hit Events in a Tennis Game Using Multimodal Information'. Volterra, Italy : KTH Computer Science and Communication 11th International Conference on Auditory-Visual Speech Processing (AVSP), Volterra, Italy: International Conference on Auditory-Visual Speech ProcessingFull text is available at: http://epubs.surrey.ac.uk/74814/
Abstract
We describe a novel framework to detect ball hits in a tennis game by combining audio and visual information. Ball hit detection is a key step in understanding a game such as tennis, but single-mode approaches are not very successful: audio detection suffers from interfering noise and acoustic mismatch, video detection is made difficult by the small size of the ball and the complex background of the surrounding environment. Our goal in this paper is to improve detection performance by focusing on high-level information (rather than low-level features), including the detected audio events, the ball’s trajectory, and inter-event timing information. Visual information supplies coarse detection of the ball-hits events. This information is used as a constraint for audio detection. In addition, useful gains in detection performance can be obtained by using and inter-ballhit timing information, which aids prediction of the next ball hit. This method seems to be very effective in reducing the interference present in low-level features. After applying this method to a women’s doubles tennis game, we obtained improvements in the F-score of about 30% (absolute) for audio detection and about 10% for video detection.
- . (2011) 'Transductive Transfer Learning for Action Recognition in Tennis Games'. 3rd International Workshop on Video Event Categorization, Tagging and Retrieval for Real-World Applications (VECTaR), in conjunction with ICCV,
- .
(2011) 'An evaluation of bags-of-words and spatio-temporal shapes for action recognition'. 2011 IEEE Workshop on Applications of Computer Vision, WACV 2011, , pp. 344-351.Full text is available at: http://epubs.surrey.ac.uk/74813/
Abstract
Bags-of-visual-Words (BoW) and Spatio-Temporal Shapes (STS) are two very popular approaches for action recognition from video. The former (BoW) is an un-structured global representation of videos which is built using a large set of local features. The latter (STS) uses a single feature located on a region of interest (where the actor is) in the video. Despite the popularity of these methods, no comparison between them has been done. Also, given that BoW and STS differ intrinsically in terms of context inclusion and globality/locality of operation, an appropriate evaluation framework has to be designed carefully. This paper compares these two approaches using four different datasets with varied degree of space-time specificity of the actions and varied relevance of the contextual background. We use the same local feature extraction method and the same classifier for both approaches. Further to BoW and STS, we also evaluated novel variations of BoW constrained in time or space. We observe that the STS approach leads to better results in all datasets whose background is of little relevance to action classification. © 2010 IEEE.
- .
(2010) 'BALL EVENT RECOGNITION USING HMM FOR AUTOMATIC TENNIS ANNOTATION'. Proceedings of Intl. Conf. on Image Proc., Full text is available at: http://epubs.surrey.ac.uk/123379/
- . (2010) 'Lattice-based Anomaly Rectification for Sport Video Annotation'. Proceedings of ICPR 2010,
- . (2010) 'Unified graph matching in Euclidean spaces'. San Francisco : IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
- . (2010) 'Anomaly Detection and Knowledge Transfer in Automatic Sports Video Annotation'. Proceedings of DIRAC Workshop on Detection and Identification of Rare Audivisual Cues, Barcelona, Spain: DIRAC Workshop on Detection and Identification of Rare Audivisual Cues, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
- . (2009) 'Hierarchical Image-Region Labeling via Structured Learning'. London : Proceedings of the British Machine Vision Conference,
- . (2009) 'CHARACTER RECOGNITION IN NATURAL IMAGES'. INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, Lisbon, PORTUGAL: 4th International Conference on Computer Vision Theory and Applications, pp. 273-280.
- . (2008) 'Can relevance of images be inferred from eye movements?'. Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval, Vancouver, Canada: MIR '08
- . (2006) 'Regression-based Hand Pose Estimation from Multiple Cameras'. New York : Proceedings of the Conference on Computer Vision and Pattern Recognition,
- . (2006) 'Directing the attention of a wearable camera by pointing gestures'. IEEE COMPUTER SOC SIBGRAPI 2006: XIX Brazilian Symposium on Computer Graphics and Image Processing, Proceedings, Manaus, BRAZIL: 19th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2006), pp. 179-186.
- . (2003) 'Active Vision forWearables'. Eurowearable,
- . (2002) 'Head pose estimation for wearable robot control'. Cardiff, Wales : British Machine Vision Conference (BMVC),
- . (2001) 'Feature Selection Based on Fuzzy Distances Between Clusters: First Results on Simulated Data'. Rio de Janeiro, Brazil : International Conference on Advances in Pattern Recognition (ICAPR),
- . (2000) 'Improved Face x Non-Face Discrimination Using Fourier Descriptors Through Feature Selection'. Gramado, Brazil : SIBGRAPI,
- . (2000) 'Eigenfaces versus Eigeneyes: First Steps Toward Performance Assessment of Representarions for Face Recognition'. Acapulco, Mexico : MICAI,
- . (2000) 'Detection and Tracking of Facial Features in Video Sequences'. Acapulco, Mexico : MICAI,
- . (2000) 'A Framework for Face Recognition from Video Sequences Using GWN and Eigenfeature Selection'. Atibaia, Brazil : WAICV,
Books
- . (2012) Proceedings of the 4th UK Computer Vision Student Workshop (BMVW). BMVA
Book chapters
- . (2012) 'Anomaly Detection and Knowledge Transfer in Automatic Sports Video Annotation'. in Weinshall D, Anemüller J, van Gool L (eds.) Detection and Identification of Rare Audiovisual Cues Springer 384, pp. 109-117.
Patents
- . (2009) Unified graph matching in Euclidean spaces and applications to image comparison and retrieval. USA: Article number 12571630
- . (2009) Consistent hierarchical labeling of image and image regions. USA: Article number 12546948
- . (2009) Modeling Images as sets of Weighted Features. USA, Europe: Article number 12361235
- . (2008) Method of and apparatus for processing image data for display by a multiple-view display device. USA, Japan, UK, Europe: Article number 12523450
Reports
- . (2010) Images as Sets of Locally Weighted Features. Guildford, UK : Article number VSSP-TR-1/2010
Theses and dissertations
- . (2006) 3D Visual Tracking of Articulated Objects and Hands.
Follow this link for my recent papers.
My older papers and my thesis are downloadable from Oxford.
Here is a link to my DBLP entry and here is the link to my MS Academic profile.
Further activities
- I've lead Surrey's effort to join the PASCAL2 network of excellence and now I'm the local site manager (see my PASCAL profile). This should increase our collaboration with PASCAL members and promote more machine learning activity in this research centre.
- I'm helping with the organisation of BMVC 2012 and I'm chairing the students' workshop
- I served as one of the area chairs of VISAPP 2012
- I'm co-chairing the Computer Vision sessions at the EURO 2012 conference
- I regularly review papers for journals such as Pattern Recognition, PR Letters, Image and Vision Computing, IEEE TIP, and for conferences such as ICCV, ECCV, CVPR, ACCV, ICPR, CIARP, Sibgrapi and a number of workshops.
