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<p>Hardware, software tools, algorithms, and performance metrics that have been developed for image understanding are presented. Three commercially built examples reflecting three mature approaches considered germane to vision-single-instruction multiple-data, multiple-instruction multiple-data, and systolic processing-were chosen. They are, respectively, the Connection Machine, the Butterfly, and the Warp. A fourth approach, more specific to vision, was also selected for noncommercial implementation. This machine, the Image-Understanding Architecture, involves a heterogeneous combination of parallel processors with single-instruction multiple-data, multiple-instruction multiple-data, and other capabilities. Each site employing one of the above architectures developed a different set of tools, leading to significant cross-fertilization of ideas between the sites. Algorithms for low-level vision, shape from texture, fusing stereo and texture, surface interpolation, and robot navigation, among others, are briefly discussed. Benchmarks are described.</p>
Christopher Brown, Jon A. Webb, Charles C. Weems, Tomaso Poggio, John R. Kender, "Parallel Processing in the DARPA Strategic Computing Vision Program", IEEE Intelligent Systems, vol. 6, no. , pp. 23-38, October 1991, doi:10.1109/64.97789
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