期刊
PATTERN RECOGNITION
卷 93, 期 -, 页码 228-236出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2019.04.023
关键词
Gait recognition; Soft biometrics; Joint learning; Network visualization
资金
- National Key Research and Development Program of China [2016YFB1001000]
- National Natural Science Foundation of China [61525306, 61633021, 61572504, 61420106015]
- Beijing Natural Science Foundation [4162058]
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. (C) 2019 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据