Robust motion segmentation for on-line application
- When?
- Wednesday 1 August 2012, 11:00 to 12:00
- Where?
- CVSSP Seminar Room (40bAB05)
- Open to:
- Public, Staff, Students
- Speaker:
- Dr Vítězslav Beran, Department of Computer Graphics and Multimedia, Brno University of Technology, Czech Republic
1st talk
Title: Robust motion segmentation for on-line application
Abstract: The seminar presents an approach for on-line video motion segmentation. Common methods were designed for off-line processing, where time to process one frame is not so important and varies from minutes to hours. The motivation of our work was an application in robotic perception, where a high computational speed is required. The main contribution of this work is an adaptation of existing methods to a higher computational speed and on-line processing. The proposed approach is based on sparse features, we utilized the KLT tracker to obtain their trajectories. A RANSAC-based method is used for initial motion segmentation, resulting motion groups are partitioned by a spatial-proximity constraints. The correspondence of motion groups across frames is solved by one-frame label
propagation in forward and backward directions. Finally, an approximation of dense image segmentation is obtained by
using the Voronoi tessellation.
2nd talk
Title: Fast and Accurate Plane Segmentation in Depth Maps for Indoor Scenes
Abstract: This paper deals with a scene pre-processing task – depth image segmentation. Efficiency and accuracy of several methods for depth map segmentation are explored. To meet the real-time capable constraints, state-of-the-art techniques needed to be optimized and modified. Along with these modifications, new segmentation approaches are presented which aim at optimizing performance characteristics. They benefit from an assumption of human-made indoor environments by focusing on detection of planar regions. All methods were evaluated on datasets with manually annotated real environments. A comparison with alternative solutions is also presented.
