GPGPU implementation of visual tracking by particle filter with pixel ratio likelihood

Visual tracking by particle filter with pixel ratio in a region of interest for likelihood computation has wide range of applications despite of its simple algorithm. A GPGPU (General Purpose computation on Graphics Processing Unit) implementation of the visual tracking in parallel computation has been proposed in this paper. Algorithm of the tracker has almost fully been implemented in CUDA framework. Difference of the proposed algorithm from the full algorithm is a reduction of image size from the original image in order to deal with multiple images for likelihood computation in limited size of constant memory of the GPU hardware. Performance of the proposed method achieves 30 fps (frame per second) for specific colored object tracing task and more than ten frame per second for a task of hands tracking of a car driver operating a steering.