Artificial Intelligence
International Journal of Computer Vision
Inferring global perceptual contours from local features
International Journal of Computer Vision - Special issue on computer vision research at the University of Southern California
International Journal of Computer Vision
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Perceptual organization of occluding contours of opaque surfaces
Computer Vision and Image Understanding - Special issue on perceptual organization in computer vision
Computational Framework for Segmentation and Grouping
Computational Framework for Segmentation and Grouping
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shocks from images: propagation of orientation elements
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Segmentation of Spontaneously Splitting Figures into Overlapping Layers
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
A computational approach to illusory contour perception based on the tensor voting technique
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
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We propose a method to generate component-based shape descriptions by the application of a perceptual grouping approach known as tensor voting. Based on previously described results on the generation of region, curve and junction saliencies and motivated by psychological findings about shape perception, we introduce extensions by a voting between junctions to create amodal completions, by a labeling of the junctions according to a catalog of junction types, and by a traversal algorithm to collect the local information into globally consistent part decompositions. In contrast to commonly used partitioning schemes, our method is able to create layered representations of overlapping parts. We consider this a major advantage together with the use of local operations and low computational costs whereas other approaches are based on highly iterative processes.