Image Processing for Multiple-Target Tracking on a Graphics Processing Unit - Michael A Tanner
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Présentation Image Processing For Multiple - Target Tracking On A Graphics Processing Unit de Michael A Tanner Format Broché
- Livre Science humaines et sociales, Lettres
Résumé : Multiple-target tracking (MTT) systems have been implemented on many di erent platforms, however these solutions are often expensive and have long development times. Such MTT implementations require custom hardware yet o er very little flexibility with ever changing data sets and target tracking requirements. This research explores how to supplement and enhance MTT performance with an existing graphics processing unit (GPU) on a general computing platform. Typical computers are already equipped with powerful GPUs to support various games and multimedia applications. However, such GPUs are not currently being used in desktop MTT applications. Bottleneck MTT image processing functions (frame di erencing) were converted to execute on the GPU. On average, the GPU code executed 287% faster than the MATLAB implementation. Some individual functions actually executed 20 times faster than the baseline. These results indicate that the GPU is a viable source to signi cantly increase the performance of MTT with a low-cost hardware solution. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Sommaire:
Multiple-target tracking (MTT) systems have been implemented on many di erent platforms, however these solutions are often expensive and have long development times. Such MTT implementations require custom hardware yet o er very little flexibility with ever changing data sets and target tracking requirements. This research explores how to supplement and enhance MTT performance with an existing graphics processing unit (GPU) on a general computing platform. Typical computers are already equipped with powerful GPUs to support various games and multimedia applications. However, such GPUs are not currently being used in desktop MTT applications. Bottleneck MTT image processing functions (frame di erencing) were converted to execute on the GPU. On average, the GPU code executed 287% faster than the MATLAB implementation. Some individual functions actually executed 20 times faster than the baseline. These results indicate that the GPU is a viable source to signi cantly increase the performance of MTT with a low-cost hardware solution.
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