基于轮廓的步态识别频域方法

Soumyadip Sengupta, Udit Halder, R. Panda, A. S. Chowdhury
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引用次数: 0

摘要

本文提出了一种基于傅立叶变换的无模型步态识别方法。首先利用傅里叶变换将步态序列转换到频域。然后分析频率分量的信息含量,确定有效频率的个数,以帮助识别过程。这些主频率被分别处理,以获得基于画廊和探针图像之间的相关系数的分数。在最后阶段将个人分数融合,得到最终分数。将该方法与其他先进的无模型步态识别算法进行了比较。USF HumanID数据库的实验结果清楚地表明了我们技术的优势。
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A frequency domain approach to silhouette based gait recognition
In this paper, we propose a frequency domain based model-free gait recognition approach from silhouette inputs using Fourier Transform. Gait sequences are first converted into frequency domain using Fourier transform. Information content of the frequency components are analysed next to determine the number of effective frequencies which can help in the recognition process. These principal frequencies are treated separately to obtain scores based on the correlation coefficient between the gallery and the probe images. The individual scores are fused in the last stage to obtain the final score. The proposed approach is compared with other state-of-the-art model-free gait recognition algorithms. Experimental results on the USF HumanID database clearly indicate the supremacy of our technique.
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