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Proceedings Paper

3D articulated object recognition: a case study
Author(s): B. Liu; Patrick S. P. Wang
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Paper Abstract

A simple method for visualizing, understanding, interpreting, and recognizing 3D objects from 2D images is presented. It extended the linear combination methods, uses parallel pattern matching and can handle 3D rigid concave objects as well as convex objects, yet, needs only a very small number of learning samples. Some real images are illustrated, with future research discussed including more complicated images such as 3D concave and articulated objects.

Paper Details

Date Published: 29 October 1996
PDF: 11 pages
Proc. SPIE 2904, Intelligent Robots and Computer Vision XV: Algorithms, Techniques,Active Vision, and Materials Handling, (29 October 1996); doi: 10.1117/12.256270
Show Author Affiliations
B. Liu, Northeastern Univ. (United States)
Patrick S. P. Wang, Northeastern 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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