2017 IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2017)

211 / 2017-01-10 16:50:15

GPU-based Backround Subtraction using CUDA:State of the Art

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Fundamental to advance video processing such as object tracking, gait recognition and video indexing is the issue of robust background modeling. Several methods have been explored regarding this application, but they are time consuming. The processing of real time video is computationally intensive. In recent years, GPUs have attracted the attention of many application developers as powerful massively parallel system. Since the GPUs provide a vast number of simple, data-parallel, multithreaded cores and high memory bandwidths, they have been used to provide a valid support in video processing research area. CUDA as a general purpose parallel computing architecture make GPUs an appealing choice to solve many complex computational problems in a more efficient way. In this paper the background subtraction techniques and relevant applications are reviewed, highlighting the advantages of using CUDA in terms of efficiency.