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GPU accelerated foreground segmentation using CodeBook model and shadow removal using CUDA

机译:GPU使用CodeBook模型加速前景分割,并使用CUDA去除阴影

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Background Subtraction is the major important step in many image processing applications which can be applied in much of video surveillances. The major result of this method is accuracy as well as processing time. So we mainly focused on these two challenges. We parallelized the Two Layered CodeBook Model on Graphical Processing Unit (GPU) for increasing the processing speed and the accuracy of the object is increased by using Shadow Removal technique in this proposed method. This algorithm uses CUDA programming language on GPU for making the computation faster when compared with the existing Two Layered CodeBook Model on CPU.
机译:背景减法是许多图像处理应用程序中的重要重要步骤,可将其应用于许多视频监控中。这种方法的主要结果是准确性和处理时间。因此,我们主要关注这两个挑战。我们在图形处理单元(GPU)上并行化了两层CodeBook模型,以提高处理速度,并在此方法中使用阴影去除技术提高了对象的准确性。与现有的CPU上的两层CodeBook模型相比,该算法在GPU上使用CUDA编程语言来提高计算速度。

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