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Proceedings Paper

Three-dimensional features of object shape: relevance for recognition and reasoning about function
Author(s): Stoyanka D. Zlateva
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Paper Abstract

THe focus of the paper is the nature and computation of features used in 3D shape representations within the context of recent research in bottom-up and top-down approaches for object recognition. Bottom-up approaches compute rich representations of low-level representations and then proceed to derive higher level features, typically using grouping heuristics and without high level knowledge. Representative of this category are computations on the primal sketch level and the 'shape from' processes. Top-down approaches specify a prototypical object shape representation and search for and verify its presence in the early representation. Representative of this category are descriptions in terms of part configurations or through deformable prototypes. The representations and associated features will be discussed in view of their usefulness for object recognition as well as for reasoning about object function. This paper compared and contrasts these approaches within the framework of a hierarchical shape representation based on a surface decomposition into the largest convex patches. It will be shown that grouping processes in bottom- up approaches directly relate to high order descriptors.

Paper Details

Date Published: 29 October 1996
PDF: 9 pages
Proc. SPIE 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling, (29 October 1996); doi: 10.1117/12.256296
Show Author Affiliations
Stoyanka D. Zlateva, Boston Univ. (United States)


Published in SPIE Proceedings Vol. 2904:
Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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