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Proceedings Paper

Model-based 3D object recognition using reciprocal basis sets and direction of arrival techniques
Author(s): David Cyganski; Richard F. Vaz; Charles R. Wright
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Paper Abstract

This paper presents a new method for model-based object recognition which uses a single, comprehensive analytic object model representing the entirety of a suite of gray-scale views of the object. In this way, object orientation and identity can be directly established from arbitrary views, even though these views are not related by any geometric image transformation. The approach is also applicable to other real and complex sensed data, such as radar and thermal signatures. The unprocessed object model is comprised of a set of basis images with complex exponential harmonic terms as coefficients. A new model is formed comprised of the reciprocal set of the object basis set. The projection of an acquired image onto the reciprocal basis thus produces samples of a complex exponential, the phase of which reveals the pose parameters. Estimation of this phase for several degrees of freedom corresponds to the plane wave direction of arrival (DOA) problem; thus the pose parameters can be found using DOA solution techniques. Results are given which illustrate the performance of a simplified, preliminary, implementation of this method using real-world images.

Paper Details

Date Published: 12 January 1993
PDF: 8 pages
Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); doi: 10.1117/12.139078
Show Author Affiliations
David Cyganski, Worcester Polytechnic Institute (United States)
Richard F. Vaz, Worcester Polytechnic Institute (United States)
Charles R. Wright, Worcester Polytechnic Institute (United States)


Published in SPIE Proceedings Vol. 1771:
Applications of Digital Image Processing XV
Andrew G. Tescher, Editor(s)

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