JANUARY 28, 2009--Consumer graphics processing units (GPUs) have experienced an extraordinary evolution in both computing performance and programmability, leading to greater use of the GPU for non-rendering applications. Now, Bryson Payne, assistant professor of computer science at North Georgia College & State University, and his colleagues have developed a real-time object tracking algorithm, based on the hybridization of particle filtering (PF) and a multiscale local search (MSLS) algorithm for both CPU and GPU architectures.
The developed system provides successful results in precise tracking of single and multiple targets in monocular video, operating in real-time at 70 frames/s for 640 x 480-pixel video resolutions on the GPU, up to 1100% faster than the CPU version of the algorithm. For more information, go to: www.gavab.es/capo/msls_pf/
