Clustering in video data: Dealing with heterogeneous semantics of features
Pattern Recognition
Video scene interpretation using perceptual prominence and mise-en-scène features
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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We investigate the role of perceptual organization in tracking 2D structures in long image sequences. Heretofore, the role of perceptual organization in computer vision has mainly been in static 2D image analysis. The role of perceptual organization in 2D motion sequence analysis has been minimal. We exploit the similarity of feature attributes between frames to track 2D structures. The incremental variation of attributes of a structure with time can be assumed to be small. This is a manifestation of the small motion assumption between frames. Even the change in location of an organization from one frame to the other can be taken to be small. This suggests that if we overlay the corresponding organizations from different frames onto one frame then we will get a highly organized pattern which exhibits the Gestalt relationships of similarity, parallelism, and proximity.