基于微多普勒特征的步态特征提取

B. Ayhan, C. Kwan, Chao Lu
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引用次数: 2

摘要

在穿墙监视(TWS)应用中,一种可能的增强方法是从微多普勒特征中提取步态特征,如躯干速度、手臂和腿部摆动运动。然后,这些步态特征可以被施加到动画人类物体的顶部以实现可视化。因此,与动画对象的可视化将更加令人信服和现实。本文总结了我们在这方面的研究成果。首先提出了一个系统的方法,然后使用人体步行仿真模型进行了一些验证实验。最后,利用实验数据提取步态特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extracting Gait Characteristics from Micro-Doppler Features
One possible enhancement in through-the-wall surveillance (TWS) applications with respect to human subject detection is to extract gait characteristics such as torso speed, and arm and leg swing motions from the micro-Doppler features. These gait characteristics can then be imposed on top of animated human objects for visualization. As a result, the visualization with the animated objects will be more convincing and realistic. This paper summarizes our results in this area. A systematic methodology is presented first, followed by some validation experiments using a human walking simulation model. Finally, experimental data were used to extract gait characteristics.
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