Abstract
This paper introduces a method to create a hierarchical description of smooth curved surfaces based on scale-space analysis. We extend the scale-space method used in 1-D signal analysis to 3-D object. A 3-D scale-space images are segmented by zero-crossings of surface curvatures at each scale and then linked between consecutive scales based on topological changes (KH-description). The KH-description is, then, parsed and translated into the PS-tree which contains the number and distribution of subregions required for shape matching. The KH-description contains coarse-to-fine shape information of the object and the PS-tree is suitable for shape matching. A hierarchical matching algorithm using the descriptions is proposed and examples show that the symbolic description is suitable for efficient coarse-to-fine 3-D shape matching.
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© 1992 Springer-Verlag Berlin Heidelberg
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Morita, S., Kawashima, T., Aoki, Y. (1992). Hierarchical shape recognition based on 3-D multiresolution analysis. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_97
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DOI: https://doi.org/10.1007/3-540-55426-2_97
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