Robust and Efficient Detection of Salient Convex Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Performance Characterization of Intermediate-Level Grouping Modules
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Design Considerations for Generic Grouping in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Human vision has marvelous ability in grouping a set of points with finite distance in between to form coherent line contour perception. This paper first suggests some general principles for computing perceptual organization and then presents a model to group points into line contours. The grouping factors arise at two levels. At the first level, grouping factors are identified as direct point-point interaction and orientation interaction. Point-point interaction is short-ranged and homogeneous. Orientation interaction is locally oriented and mediated by local visual context. At the second level, grouping factors are global geometric binding effect arising from geometric redundancy reduction. Line perception is then generally formulated as combinatorial optimization. Since it includes local, global interactions and local context effects, the model may capture partially grouping ability of human vision systems.