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1 November 1992 Selecting viewpoints for visual manufacturing systems
John E. McInroy
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Proceedings Volume 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision; (1992) https://doi.org/10.1117/12.131568
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
A technique for selecting one camera viewpoint from m viewpoints containing zero mean Gaussian errors is presented. The procedure consists of a two stage analysis. First, the joint entropy of each viewpoint is found. The viewpoint with minimum entropy possesses the greatest possible lower bound reliability of meeting any quadratic specification of the pose error. Hence it is the best pose algorithm to select without further analysis. To guarantee a minimum reliability, a second stage of analysis is necessary. Methods of calculating reliability bounds for a given quadratic specification are explained. The reliability calculations require three orders of magnitude less computations than the alternative, Monte Carlo simulations. On the other hand, reliability analysis requires an order of magnitude more computations than entropy analysis. The concepts are simulated using a visual pose measurement system developed by NASA. The results indicate that entropy is very effective for selecting pose algorithms, and the reliability greatest lower bound is close to the actual reliability.
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John E. McInroy "Selecting viewpoints for visual manufacturing systems", Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); https://doi.org/10.1117/12.131568
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KEYWORDS
Reliability
Visualization
Manufacturing
Monte Carlo methods
Cameras
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