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A comprehensive study on gait biometrics using a joint CNN-based method
Yuqi Zhang1; Yongzhen Huang1; Liang Wang1; Shiqi Yu2
发表期刊Pattern Recognition
2019
期号2019,93页码:228-236
文章类型长文
摘要

This paper gives a comprehensive study on gait biometrics via a joint CNN-based method. Gait is a kind of behavioral biometric feature with unique advantages, e.g., long-distance, cross-view and non-cooperative perception and analysis. In this paper, the definition of gait analysis includes gait recognition and gait-based soft biometrics such as gender and age prediction. We propose to investigate these two problems in a joint CNN-based framework which has been seldom reported in the recent literature. The proposed method is efficient in terms of training time, testing time and storage. We achieve the state-of-the-art performance on several gait recognition and soft biometrics benchmarks. Also, we discuss which part of the human body is important and informative for a specific task by network visualization.

关键词Gait Recognition Soft Biometrics Joint Learning Network Visualization
DOI10.1016/j.patcog.2019.04.023
URL查看原文
收录类别SCI
七大方向——子方向分类生物特征识别
国重实验室规划方向分类其他
引用统计
被引频次:71[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/23554
专题智能感知与计算
通讯作者Liang Wang
作者单位1.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
2.College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Yuqi Zhang,Yongzhen Huang,Liang Wang,et al. A comprehensive study on gait biometrics using a joint CNN-based method[J]. Pattern Recognition,2019(2019,93):228-236.
APA Yuqi Zhang,Yongzhen Huang,Liang Wang,&Shiqi Yu.(2019).A comprehensive study on gait biometrics using a joint CNN-based method.Pattern Recognition(2019,93),228-236.
MLA Yuqi Zhang,et al."A comprehensive study on gait biometrics using a joint CNN-based method".Pattern Recognition .2019,93(2019):228-236.
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