基于时空序列的运动检测

T. Zhang, Haixian Wang
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引用次数: 0

摘要

本文提出了一种新的灰度视频运动检测方法。在我们的算法中,使用多个不同长度的时空序列来过滤视频中的帧。然后将这些过滤后的图像组合在一起,得到真实的运动。我们的算法的性能用几个人类动作数据集进行了测试,其中执行了不同的动作。将本文算法的检测结果与前人的工作以及人工提取的目标进行了比较。实验结果表明,该滤波器的响应接近原始视频中人的真实动作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Motion detection with spatiotemporal sequences
In this paper we propose a new method to detect motion in a greyscale video. In our algorithm, several spatiotemporal sequences with different lengths are used to filter the frames in the video. Then these filtered images are combined together to get the real motion. The performance of our algorithm is tested with several human action datasets in which different actions are performed. The detected results of our algorithm are compared with previous works and the targets we extract manually. The experimental results show that the responses of our filter are close to the real action of the human in the original video.
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