Frontal gait recognition from incomplete rgb-d streams using gait cycle analysis

Wenyun Zou, Seiichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gait as a significant biometric feature in human identification is drawing a wide attention nowadays. In many real-life surveillance zones such as banks, airports and corridors, gait recognition is often restricted from the front view. There are situations where a complete gait cycle is not always available due to frame drop caused by devices and the limitation in space of such areas, while most of the existing methods require at least one complete gait cycle. A novel method is proposed to achieve a high recognition rate in such application scenarios, based on dividing a gait cycle into several phases using Constrained Fuzzy C-Means method and converging feature information of a stream into one feature descriptor using gait cycle analysis. Experimental results demonstrate the high performance of our method comparing to other existing ones.

Original languageEnglish
Title of host publication2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages453-458
Number of pages6
ISBN (Electronic)9781538651612
DOIs
Publication statusPublished - 2019 Feb 12
EventJoint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018 - Kitakyushu, Japan
Duration: 2018 Jun 252018 Jun 28

Publication series

Name2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018

Conference

ConferenceJoint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018
CountryJapan
CityKitakyushu
Period18/6/2518/6/28

    Fingerprint

Keywords

  • Frontal gait recognition
  • Fuzzy gait phase clas-sification
  • Gait cycle analysis
  • Incomplete gait cycle
  • RGB-D stream

ASJC Scopus subject areas

  • Signal Processing
  • Control and Optimization
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems

Cite this

Zou, W., & Kamata, S. (2019). Frontal gait recognition from incomplete rgb-d streams using gait cycle analysis. In 2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018 (pp. 453-458). [8640960] (2018 Joint 7th International Conference on Informatics, Electronics and Vision and 2nd International Conference on Imaging, Vision and Pattern Recognition, ICIEV-IVPR 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEV.2018.8640960