CUDA Implementation of The Pixel Based Adaptive Segmentation Algorithm

The operation of foreground background subtraction, which has a crucial role on video processing, needs to be processed in real time. In this paper, we present an implement of the pixel based adaptive segmentation (PBAS) algorithm on CUDA parallel programming platform to process high resolution videos in real time. The performance of the implementation is enhanced by using Nsight profiler metrics such as consumed time for functions, usage of GPU compute and memory, occupancy, divergence. Experimental evaluation on benchmark videos presents the performance of the implementation; On a Tesla K20 graphic processing unit, 646 fps is achieved for a video with 320x240 resolution when memory transfer to and from the GPU is included. As a result, about 17 time speedup is achieved with regards to single thread version.