服装变化条件下基于特征点和局部形状特征的步态识别评价

Daisuke Imoto, K. Kurosawa, K. Tsuchiya, K. Kuroki, Manato Hirabayashi, N. Akiba, H. Kakuda
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引用次数: 0

摘要

阶段DOI: 10.3408 / jafst。步态识别是最近发展起来的一项技术,我们可以通过一个人的步态来识别一个人。主要有两种方法;基于轮廓和基于模型。在日本,基于GEI(步态能量图像)的方法是一种基于轮廓的方法,用于法医目的。有时,在GEI方法下,由于diŠerent服装降低了识别可靠性,这是一个人的轮廓变化的问题。在这里,我们使用我们之前提出的动态特征方法来分析和评估服装变化条件下的平均错误率。动态特征方法是在前人基于模型的步态识别研究的启发下建立的,该方法利用特征点的时间序列和从轮廓序列中自动提取的点周围的局部形状特征。在分析之前,我们将u - isir步态数据库-跑步机数据集B-中包含侧视图数据的整个数据大致分为5个服装类别,以应对真实的oŠ-line法医情况,在这种情况下,我们无法严格控制对人体步态动态特性的利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of gait recognition using dynamics of feature points and local shape features under clothing variation conditions
 STAGE DOI: 10.3408 / jafst.745 ) Gait recognition is one of recently evolving techniques by which we can recog-nize individuals by one's gait. There are two major approaches; silhouette-based and model-based. In Japan, a method based on GEI ( Gait Energy Image ) , which is one of the silhouette-based approaches, is used for forensic purposes. Sometimes, it is a problem of silhouettes' variabilities in one person due to diŠerent clothing that les-sen recognition reliability under the GEI method. Here, we analyzed and evaluated the average error rates under clothing variation conditions using the method called Dynamic-features method, which we previously proposed. The Dynamic-features method was built inspired by previous studies of model-based gait recognition, which uses time-series of feature points and local shape features around the points automatically extracted from silhouette sequences. Before analysis, we roughly categorize whole data in the OU-ISIR gait database -treadmill dataset B-, which con-tains side-view data, into ˆve clothing categories in order to deal with realistic oŠ-line forensic situation, where we cannot strictly control utilization of dynamic properties of human's gait.
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