Human action recognition and analysis algorithm for fixed and moving cameras
Human action recognition and analysis algorithm for fixed and moving cameras
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适用于固定和移动摄像机的人体动作识别和分析算法
DOI：
10.1049/el.2015.1037
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
M. Abdelwahab
中科院分区：
文献类型：
--
作者：
M. Abdelwahab;M. Abdelwahab
提出了一种新的人体动作识别算法。提出了在多层中使用代表不同角度的光流的正面和侧面视图。从正面视图创建的of的侧视图作为一个新功能引入。它提高了识别的准确性，并提供了更多关于动作的信息，如重复次数。对得到的OF特征进行二维离散傅里叶变换，使算法对平移和对齐不敏感。利用二维主成分分析从特征空间中提取特征，保持了像素间的空间关系，提高了识别精度。与最近报道的方法相比，在Weizmann、IXMAS、KTH和UCF四个不同的数据集（代表固定和移动摄像机）上进行的实验结果证实了这些优异的性能。
A new algorithm for human action recognition is presented. The use of both front and side views of the optical flow (OF) in multiple layers representing different angles is proposed. The side view of the OF, created from the frontal view, is introduced as a new feature. It improves recognition accuracy and provides more information about the action such as the number of repetitions. Two-dimensional (2D) discrete Fourier transform is applied to the obtained OF features that makes the algorithm not sensitive to translation and alignment. 2D principal component analysis is used to extract features from the eigenspace maintaining the spatial relation between pixels and increases the recognition accuracy. Results of experiments performed on four diverse datasets, Weizmann, IXMAS, KTH, and UCF sports, representing fixed and moving cameras, confirm these excellent properties compared with recent reported methods.