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20 April 1993 Information theoretic approach to model-based 3D object recognition using orthogonal transforms
Inderpreet S. Khurana, Richard F. Vaz, David Cyganski, Charles R. Wright
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Proceedings Volume 1827, Model-Based Vision; (1993) https://doi.org/10.1117/12.143057
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
A previously reported technique for object recognition and orientation determination is used to develop an information theoretic viewpoint of the model-based vision problem. The technique employs an analytic object model developed from transform coefficients of object views, and develops pose parameter estimates by minimizing an error measure developed from the model and transform coefficients of an acquired image. Parallels between this technique and vector quantization-based coding are developed, which motivate an analysis of the machine vision system performance in terms of the distortion/rate performance achievable. This paper presents the framework for such a viewpoint, along with preliminary performance results of the recognition technique.
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Inderpreet S. Khurana, Richard F. Vaz, David Cyganski, and Charles R. Wright "Information theoretic approach to model-based 3D object recognition using orthogonal transforms", Proc. SPIE 1827, Model-Based Vision, (20 April 1993); https://doi.org/10.1117/12.143057
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KEYWORDS
3D modeling
Visual process modeling
Model-based design
Object recognition
Error analysis
Machine vision
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