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1 November 1992 Automatic vision programs from predicted features
Prasanna G. Mulgaonkar, Chien-Huei Chen, Bharath Modayur
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Proceedings Volume 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods; (1992) https://doi.org/10.1117/12.131615
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
Techniques are presented for automatically generating optimal vision programs from high- level task descriptions. Vision programs are the object models that describe strategies to recognize and locate objects in an image. The effectiveness of the program depends on the features used for recognition and the order in which the features are evaluated. We describe three probabilistic feature utility measures and a cost function based on program execution time that serve as the basis of our technique. Computation of such utility measures from a statistically representative sample of images has been demonstrated. Problems encountered in computing such measures from computer-generated images are described.
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Prasanna G. Mulgaonkar, Chien-Huei Chen, and Bharath Modayur "Automatic vision programs from predicted features", Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); https://doi.org/10.1117/12.131615
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KEYWORDS
Visual process modeling
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