Image Processing on the GPU: a Canonical Example
نویسندگان
چکیده
Recent computer vision work at Berkeley has focused on tracking both human and animal motion in a sequence of images [1]. The most costly stage of the tracking algorithm is searching through a given frame for recognizable limbs at different orientations. In this project, we propose using the GPU as a means of parallelizing the search problem. The use of the GPU for this canonical vision problem is an extension of recent work demonstrated by Moreland and Angel [2]. By transforming the tracking algorithm into various stages of a modified rendering pipeline, we achieve a performance increase ten times that of an algorithm solely implemented on a high-end CPU.
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