JOURNAL ARTICLE

<title>Part hierarchies of object shape for recognition</title>

Stoyanka D. ZlatevaMarie‐Christine Jaulent

Year: 1994 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2353 Pages: 120-128   Publisher: SPIE

Abstract

Theoretical studies of visual form perception have proposed hierarchical representations of three dimensional shape as a basis for achieving fast and reliable recognition of a wide range of objects. In this article we relate an earlier developed representation of object shape to two different types of recognition processes: (1) recognition of familiar objects, and, (2) recognition of the possible uses or affordances of not necessarily known objects in actions. The representation is based on the connectedness and neighborhood relations of object shape. It consists of three hierarchy levels of parts, sub-parts and surface patches, which build topologies of increasing strength. Each level has an associated set of qualitative and quantitative features. We submit that the visual knowledge needed for recognizing a known object is made explicit primarily at the part level and knowledge about affordances at the sub- part level. Recognition of the possible uses of objects is treated as finding the compatibility between action requirements and object affordances. The possibility and necessity of fuzzy sets are used as measures for the compatibility of the individual requirement-affordance pairs and their aggregation to the overall compatibility of a given object and action.

Keywords:
Affordance Computer science Social connectedness Compatibility (geochemistry) Cognitive neuroscience of visual object recognition Perception Artificial intelligence Object (grammar) Representation (politics) Object-oriented design Hierarchy Pattern recognition (psychology) Human–computer interaction Object-oriented programming

Metrics

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Cited By
0.00
FWCI (Field Weighted Citation Impact)
0
Refs
0.19
Citation Normalized Percentile
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Topics

Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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