Author :
Weems, Charles C. ; Brown, Christopher ; Webb, Jon A. ; Poggio, Tomaso ; Kender, J.R.
Author_Institution :
Massachusetts Univ., Amherst, MA, USA
Abstract :
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.<>
Keywords :
computer vision; computerised pattern recognition; computerised picture processing; parallel machines; performance evaluation; Butterfly; Connection Machine; DARPA computer vision; Image-Understanding Architecture; Warp; image understanding; low-level vision; multiple-instruction multiple-data; parallel processors; performance metrics; robot navigation; shape from texture; single-instruction multiple-data; software tools; stereo; surface interpolation; systolic processing; Computer vision; Concurrent computing; Hardware; Interpolation; Measurement; Parallel processing; Shape; Software algorithms; Software tools; Surface texture;