Simultaneous Human detection and action recognition employing 2DPCA-HOG

机译：使用2dpca-hog的同时的人类检测和行动识别

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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：本文介绍了一种新的人类检测和动作识别算法。该算法基于应用于定向梯度（HOG）直方图的二维主成分分析（2DPCA）。由于采用相同算法的同时人类检测和动作识别，计算复杂性降低到大量交易。与最近的方法相比，应用于公共数据集的实验结果确认了这些优异的性能。

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《IEEE International Midwest Symposium on Circuits and Systems》|2011年||共4页
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Naiel Mohamed A.; Abdelwahab Moataz M.; Elsaban M.; Mikhael Wasfy B.;
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Simultaneous Human detection and action recognition employing 2DPCA-HOG

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