Side view face recognition as an aid to gait recognition

Kyongsae Oh; Heesung Lee; Sungjun Hong; Euntai Kim

doi:10.14864/softscis.2006.0.490.0

SCIS & ISIS 2006

Session ID : TH-J3-4

DOI https://doi.org/10.14864/softscis.2006.0.490.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

TH-J3 Computational Intelligence (2)

Side view face recognition as an aid to gait recognition

*Kyongsae Oh, Heesung Lee, Sungjun Hong, Euntai Kim

Author information

Keywords: Side view face recognition, Independent component analysis (ICA), Belief information

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

In this paper, a new method is proposed to recognize human side view faces in a video stream. This work is aimed at ultimately being used as an aid for the gait recognition because the gait biometric alone is not enough for the reliable identification. We employ a probabilistic approach to fuse the information in the successive video frames. In the proposed method, we use the ICA (FastICA), histogram filter, to extract features from side view face images and then employ PSVM (Probability SVM) as a classifier in the probabilistic framework. Experimental result shows the suggested method is valid and effective for the identification in a video stream.

Corresponding author

Register with J-STAGE for free!