The gait and face image processing

DOI

10.2991/ameii-16.2016.247How to use a DOI?

Keywords

Multi-Biometric Features Classification, Gait Classification, Facial Image Classification, Multivariate Discriminant Analysis for Matrix Component Analysis of Dichroic Image

Abstract

Dealt with the deficiency of single creature feature classification, classification methods of gait and facial side integrating at the feature layers are brought forth to improve the identify classification rate with long distance. This paper respectively has feature extraction and dimension reduction process for analyzing gait energy diagram and side facial image by multivariate discriminant analysis for Matrix component analysis of dichroic image to get original feature matrix to make vectorication, fusing feature eigenvector, and then feature fusion for fusing feature eigenvector by multiple discriminant analysis techniques to obtain the fusing eiqenvector of gait and facial image, at final nearest neighbour methods identifies identity. Testing for the above-mentioned data by CASIA Dataset B gait database. The results show that it improves the accurate classification rate to test the effectiveness of this method providing a new way for multi-biometric features classification.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongli Liu
AU  - LiYing Ye
PY  - 2016/04
DA  - 2016/04
TI  - The gait and face image processing
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.247
DO  - 10.2991/ameii-16.2016.247
ID  - Liu2016/04
ER  -