Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Probabilistic Detection and Tracking of Motion Boundaries
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Qualitative Spatiotemporal Analysis Using an Oriented Energy Representation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Bayesian inference of visual motion boundaries
Exploring artificial intelligence in the new millennium
Motion Feature Detection Using Steerable Flow Fields
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
International Journal of Computer Vision
International Journal of Computer Vision
Fitting models to distributed representations of vision
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Interest point detection and scale selection in space-time
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Detecting spatiotemporal structure boundaries: beyond motion discontinuities
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Hi-index | 0.00 |
Visual motion boundaries provide a powerful cue for the perceptual organization of scenes. Motion boundaries are present when surfaces in motion occlude one another. Conventional approaches to motion analysis have relied on assumptions of data conservation and smoothness, which has made analysis of motion boundaries difficult. We show that a common source of motion boundary, kinetic occlusion, can be detected using spatiotemporal junction analysis. Junction analysis is accomplished by utilizing distributed representations of motion used in models of human visual motion sensing. By detecting changes in the direction of motion in these representations, spatiotemporal junctions are detected in a manner which differentiates accretion from deletion. We demonstrate successful occlusion detection on spatiotemporal imagery containing occluding surfaces in motion.