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Simultaneous Human detection and action recognition employing 2DPCA-HOG

机译:使用2DPCA-HOG同时进行人类检测和动作识别

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In this paper a novel algorithm for Human detection and action recognition in videos is presented. The algorithm is based on Two-Dimensional Principal Components Analysis (2DPCA) applied to Histogram of Oriented Gradients (HOG). Due to simultaneous Human detection and action recognition employing the same algorithm, the computational complexity is reduced to a great deal. Experimental results applied to public datasets confirm these excellent properties compared to most recent methods.
机译:本文提出了一种新颖的视频中人检测和动作识别算法。该算法基于应用于方向梯度直方图(HOG)的二维主成分分析(2DPCA)。由于采用相同算法同时进行人体检测和动作识别,因此大大降低了计算复杂度。与最新方法相比,应用于公共数据集的实验结果证实了这些优异的性能。

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