基于时间梯度模式的步态识别

Jashila Nair Mogan, C. Lee, A. Tan
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引用次数: 10

摘要

提出了一种基于时间梯度模式的步态识别方法。该方法首先计算每张图像中轮廓的梯度。随后,每个像素的梯度决定像素所属的bin号。当前帧和下一帧的帧数共同对定向梯度矩阵中相应的索引进行投票。由此得到的矩阵对步态周期中每个像素点的梯度模式进行编码。TGP方法不仅可以描述空间轮廓形状,而且可以在时间轴上隐式捕获轮廓变形。实验结果表明,该方法取得了较好的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait recognition using temporal gradient patterns
In this paper, a Temporal Gradient Patterns (TGP) method is proposed for gait recognition. The method first computes the gradients of the silhouette in each image. Subsequently, the gradient of each pixel determines the bin number to which the pixel belongs to. The bin number of current and next frame jointly cast a vote to the corresponding index in the matrix of oriented gradients. The obtained matrix henceforth encodes the gradient pattern of each pixel in the gait cycle. The TGP method not only describes the spatial silhouette shapes but also implicitly captures the silhouette deformation in temporal axis. Experimental results show that the proposed approach attains a promising recognition rates.
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