• Opto-Electronic Engineering
  • Vol. 44, Issue 4, 468 (2017)
Jing Luo1、2、3, Chunyuan Zi1、2, Jianliang Zhang1、2, and Yue Liu1、2
Author Affiliations
  • 1Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China
  • 2College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China
  • 3School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, NSW 2522, Australia
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    DOI: 10.3969/j.issn.1003-501x.2017.04.003 Cite this Article
    Jing Luo, Chunyuan Zi, Jianliang Zhang, Yue Liu. Gait recognition using GEI and Curvelet[J]. Opto-Electronic Engineering, 2017, 44(4): 468 Copy Citation Text show less

    Abstract

    International and domestic academics are attracted by biometric features recognition, because the intelligent monitor-ing, which is the basis of social security, is more and more required by people. Compared with other biometric features (face, iris fingerprint and so on), gait feature has its advantages, such as acceptability, noninvasiveness, hard to hide and easy to be collected. Gait recognition, recognizing different persons by the way of his/her walking, which has some ad-vantages such as non-contact, low demand in image quality and difficult disguise, is the most potentially biological recognition technology by the way of one’s walking. Recently, the research of gait recognition is a hot topic in the field of computer vision, entrance guard system and medical diagnose, which has extensive realistic significance and wide ap-plying foreground.
    Jing Luo, Chunyuan Zi, Jianliang Zhang, Yue Liu. Gait recognition using GEI and Curvelet[J]. Opto-Electronic Engineering, 2017, 44(4): 468
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