Gait recognition by fluctuations
Gait recognition by fluctuations
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DOI：
10.1016/j.cviu.2014.05.004
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发表时间：
2014-09-01
影响因子：
4.5
通讯作者：
Yagi, Yasushi
中科院分区：
文献类型：
--
作者：
Aqmar, Muhammad Rasyid;Fujihara, Yusuke;Yagi, Yasushi
本文提出了一种利用步态波动进行步态识别的方法。由于时间波动的影响，匹配的步态图像序列之间的相位不一致会降低步态识别的性能。我们通过生成具有相等相位间隔的相位归一化步态图像序列来去除时间波动。如果步态图像序列内的周期间步态波动被重复观察到相同的对象，它们可以被视为一个有用的区别步态特征。我们提取相位波动作为时间波动，以及步态波动图像和轨迹波动作为空间波动。我们将它们与匹配分数相结合，使用相位归一化图像序列作为分数级融合框架中的额外匹配分数或作为分数归一化框架中的质量度量。我们在实验中使用大规模的公开数据库的方法进行评估，并显示所提出的方法的有效性。(C)2014爱思唯尔公司All rights reserved.
This paper describes a method of gait recognition by suppressing and using gait fluctuations. Inconsistent phasing between a matching pair of gait image sequences because of temporal fluctuations degrades the performance of gait recognition. We remove the temporal fluctuations by generating a phase-normalized gait image sequence with equal phase intervals. If inter-period gait fluctuations within a gait image sequence are repeatedly observed for the same subject, they can be regarded as a useful distinguishing gait feature. We extract phase fluctuations as temporal fluctuations as well as gait fluctuation image and trajectory fluctuations as spatial fluctuations. We combine them with the matching score using the phase-normalized image sequence as additional matching scores in the score-level fusion framework or as quality measures in the score-normalization framework. We evaluated the methods in experiments using large-scale publicly available databases and showed the effectiveness of the proposed methods. (C) 2014 Elsevier Inc. All rights reserved.