基于三维深度数据的人体运动轨迹识别

Zheng Chang, Qing Shen, X. Ban, Jing Guo
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引用次数: 2

摘要

摘要基于传统的机器视觉识别技术对人体运动轨迹的识别,找出了传统识别技术的不足。将三维深度数据、三维运动历史图像和计算出的三维运动历史图像的不变矩作为人体运动的特征向量相结合,将该方法应用于人体运动轨迹的机器视觉。详细介绍了基于三维深度数据的人体运动轨迹识别算法和实现方案。最后,通过与识别实验结果的对比,验证了基于三维数据的人体运动轨迹识别技术方法具有更准确的识别率和更好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of Human Body Movements Trajectory Based on the Three-Dimensional Depth Data
Abstract based on the traditional machine vision recognition technology about human body movement trajectory, the paper finds out the shortcomings of the traditional recognition technology. By combining the three - dimensional depth data, the three-dimensional motion history image and the invariant moments of the three - dimensional motion history image computed as the eigenvector of body movements, the paper applies the method to the machine vision of the human body movements trajectory. In detail, the paper describes the algorithm and realization scheme of the human body movements trajectory recognition based on the three-dimensional depth data. Finally, comparing with the results of the recognition experiment, we verify that the method of human body movement trajectory recognition technology based on the three-dimensional data has a more accurate recognition rate and a better robustness.
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