The visual features most important for object recognition are those having to do with the shape of an object. In one approach to recognition The image is decomposed an image into a set of relatively simple shapes (parts) and predicates that describe these parts and the relationships between them. Recognition is a matter of matching this parts-relations description to some parts-relations model in a large database of models. Matching is computationally intensive; unless the parts-relations representation is organized for efficient indexing, recognition times get intractably long. We review general requirements for such a representation as proposed by Marr and Nishihara. Their prescription leaves open general questions that must be answered in any particular implementation. We offer some solutions for a simple domain of 2-D sticklike objects and point out some aspects of the implementa-tion that might be useful for shape indexing in other domains.
Gene R. Gindi,
Donald H. Delorie,
"Indexing Shapes for Recognition", Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987); doi: 10.1117/12.937709; https://doi.org/10.1117/12.937709