Motion recognition using local auto-correlation of space-time gradients
Motion recognition using local auto-correlation of space-time gradients
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DOI：
10.1016/j.patrec.2012.01.007
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发表时间：
2012-07
期刊：
影响因子：
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通讯作者：
Takumi Kobayashi;N. Otsu
中科院分区：
文献类型：
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作者：
Takumi Kobayashi;N. Otsu
在本文中，我们提出了一种新的方法的运动特征提取的基础上的运动识别方案。该特征提取方法利用视频序列中三维运动形状的时空梯度的自相关性。该方法有效地利用了梯度的局部关系，对应于运动的时空几何特征。对于识别运动，我们应用框架的袋帧功能，这与标准的袋的功能框架，使运动特征被充分捕获和运动被快速识别的框架。在各种运动识别数据集上的实验中，与其他方法相比，该方法表现出良好的性能，计算时间甚至比真实的时间更快。
In this paper, we propose a motion recognition scheme based on a novel method of motion feature extraction. The feature extraction method utilizes auto-correlations of space–time gradients of three-dimensional motion shape in a video sequence. The method effectively exploits the local relationships of the gradients corresponding to the space–time geometric characteristics of the motion. For recognizing motions, we apply the framework of bag-of-frame-features, which, in contrast to the standard bag-of-features framework, enables the motion characteristics to be captured sufficiently and the motions to be quickly recognized. In experiments on various datasets for motion recognition, the proposed method exhibits favorable performances as compared to the other methods, and faster computational time even than real time.