Date of Award
Master of Science in Computer Engineering
Department of Electrical and Computer Engineering
Yong C. Kim, PhD
Multiple-target tracking (MTT) systems have been implemented on many different platforms, however these solutions are often expensive and have long development times. Such MTT implementations require custom hardware, yet offer 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. This research explores if and how a GPU can be used to supplement and enhance MTT implementations on a flexible common desktop computer without requiring costly dedicated MTT hardware and software. A MTT system was developed in MATLAB to provide baseline performance metrics for processing 24-bit, 1920x1080 color video footage filmed at 30 frames per second. The baseline MATLAB implementation is further enhanced with various custom C functions to speed up the MTT implementation for fair comparison and analysis. From the MATLAB MTT implementation, this research identifies potential areas of improvement through use of the GPU. The bottleneck image processing functions (frame differencing) 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 significantly increase the performance of MTT with a low-cost hardware solution.
DTIC Accession Number
Tanner, Michael A., "Image Processing for Multiple-Target Tracking on a Graphics Processing Unit" (2009). Theses and Dissertations. 2569.