Recognizing Face Profiles in the Presence of Hairs/glasses Interferences

File Size Format
67695_1.pdf 433Kb Adobe PDF View
Title Recognizing Face Profiles in the Presence of Hairs/glasses Interferences
Author Chen, Weiping; Gao, Yongsheng
Publication Title 11th International Conference on Control, Automation, Robotics and Vision (ICARCV) 2010 Proceedings
Editor IEEE
Year Published 2010
Place of publication Singapore
Publisher IEEE
Abstract Facial profile provides a complementary structure of the face that is not present in frontal faces, which has been used in personal identification, face perception research and 3D face construction. In this paper, we present a novel local attributed string matching (LAStrM) approach to recognize face profiles in the presence of interferences. The conventional profile recognition algorithms heavily depend on the accuracy of the facial area cropping. However, in realistic scenarios the facial area may be difficult to localize due to interferences (e.g., glasses, hairstyles). The proposed approach is able to efficiently find the most discriminative local parts between face profiles addressing the recognition problem with interferences. Experimental results have shown that the proposed matching scheme is robust to interferences compared against several primary approaches using two profile image databases (Bern and FERET). It has potential capability for partially occluded shape classification.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1109/ICARCV.2010.5707792
Copyright Statement Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 9781424478132
Conference name The 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010)
Location Singapore
Date From 2010-12-07
Date To 2010-12-10
URI http://hdl.handle.net/10072/38069
Date Accessioned 2011-01-31
Date Available 2011-04-18T06:56:40Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computer Vision
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

Show simple item record

Griffith University copyright notice