Abstract
We describe a method to decompose binary 2-D shapes into layers of overlapping parts. The approach is based on a perceptual grouping framework known as tensor voting which has been introduced for the computation of region, curve and junction saliencies. Here, we discuss extensions for the creation of modal/amodal completions and for the extraction of overlapping parts augmented with depth assignments. Advantages of this approach are from a conceptual point of view the close relation to psychological findings about shape perception and regarding technical aspects a reduction of computational costs in comparison with other highly iterative methods.
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Massad, A., Mertsching, B. (2001). Segmentation of Spontaneously Splitting Figures into Overlapping Layers. In: Radig, B., Florczyk, S. (eds) Pattern Recognition. DAGM 2001. Lecture Notes in Computer Science, vol 2191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45404-7_4
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DOI: https://doi.org/10.1007/3-540-45404-7_4
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