Parts of Visual Form: Computational Aspects
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Shock Graphs and Shape Matching
International Journal of Computer Vision
Motorcycle graphs and straight skeletons
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Straight Skeletons for General Polygonal Figures in the Plane
COCOON '96 Proceedings of the Second Annual International Conference on Computing and Combinatorics
Eliciting perceptual ground truth for image segmentation
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
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We propose a novel type of decomposition for polygonal shapes. It is thought that, for the task of object recognition, the human visual system uses a part-based representation. Decompositions based on skeletons have been previously proposed in computer vision. Our method is the first one, however, based on the straight line skeleton. Compared to the medial axis, the straight line skeleton has a few advantages: it contains only straight segments and has a lower combinatorial complexity. The skeletal nodes and the way they are generated are the basis for our decomposition, which has two stages that result in a hierarchical decomposition into overlapping parts. First, a number of visually striking parts are identified, then their boundaries are successively simplified, by locally removing detail. Our method runs in time O((n + r22) log2 n), after the skeleton construction, where r2 is the number of reflex edge annihilations. The decomposition is invariant to rigid motions and uniform scalings. We present results indicating that it provides natural decompositions for a variety of shapes. This makes it attractive for shape based matching in content-based image retrieval, for example.