Fusion of multiple Gait features for human identification

Sungjun Hong, Heesung Lee, Sung Je An, Euntai Kim

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

3 Citations (Scopus)

Abstract

Gait recognition has recently attracted increasing interest from the biometric community. In this paper, we propose a simple new feature called multi-bipolarized contour mean (MBCM) for gait recognition. The proposed MBCM feature consists of four components: (1) the vertical positive contour mean, (2) the vertical negative contour mean, (3) the horizontal positive contour mean, and (4) the horizontal negative contour mean. We fuse the proposed gait features at a feature level to improve recognition performance. The proposed recognition system is evaluated with the NLPR gait database.

Original languageEnglish
Title of host publication2008 International Conference on Control, Automation and Systems, ICCAS 2008
Pages2121-2125
Number of pages5
DOIs
Publication statusPublished - 2008 Dec 1
Event2008 International Conference on Control, Automation and Systems, ICCAS 2008 - Seoul, Korea, Republic of
Duration: 2008 Oct 142008 Oct 17

Publication series

Name2008 International Conference on Control, Automation and Systems, ICCAS 2008

Other

Other2008 International Conference on Control, Automation and Systems, ICCAS 2008
CountryKorea, Republic of
CitySeoul
Period08/10/1408/10/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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    Hong, S., Lee, H., An, S. J., & Kim, E. (2008). Fusion of multiple Gait features for human identification. In 2008 International Conference on Control, Automation and Systems, ICCAS 2008 (pp. 2121-2125). [4694446] (2008 International Conference on Control, Automation and Systems, ICCAS 2008). https://doi.org/10.1109/ICCAS.2008.4694446