Angle Densities and Recognition of 3D Objects

Authors:
Raashid Malik;Taegkeun Whangbo
Affiliations:
-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1997

Citing 4
Cited 1

Three-dimensional object recognition

ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
Model-based recognition in robot vision

ACM Computing Surveys (CSUR)
The Probabilistic Peaking Effect of Viewed Angles and Distances with Application to 3-D Object Recognition

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Indexing without Invariants in 3D Object Recognition

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Abstract

Recognition of 3D objects using computer vision is complicated by the fact that geometric features vary with view orientation. An important factor in designing recognition algorithms in such situations is understanding the variation of certain critical features such as angles. In this paper we derive the two dimensional joint density function of two angles in a scene given an isotropic view orientation and an orthographic projection. The analytic expression for the densities are useful in determining statistical decision rules to recognize surfaces and objects. Experiments to evaluate the usefulness of the proposed methods are reported.