基于步态的人识别

M. Zhassuzak, A. Turegali, Y. Amirgaliyev, Z. Buribayev
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引用次数: 0

摘要

步态是一种特殊的特征,需要识别,因为它影响到身体的许多部位。每个人的步态都是不同的。与指纹或视网膜识别不同,步态可以在很远的距离识别,而无需直接接触。此外,在疫情期间,步态识别比面部识别更相关。使用机器学习算法,你可以训练神经网络来识别每个人的身份。该研究考虑将流分割成帧和各种背景分割选项,如GrabCut和Mask R-CNN。下面详细分析了基于轮廓和边界框的人格识别最优解方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait Based Person Recognition
The gait is a special feature that needs to be identified as it affects many parts of the body. Each person's gait is individual. Unlike fingerprint or retinal identifiers, gait can be recognized at a great distance without direct contact. Also, gait recognition during epidemic periods is more relevant than face recognition. Using machine learning algorithms, you can train a neural network to recognize the identity of each person. The study considers splitting the stream into frames and various options for background segmentation such as GrabCut and Mask R-CNN. What follows is a detailed analysis of the optimal solution methods for human personality recognition based on the outline and the bounding box.
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