Face Detection using Half-Face Templates
Author(s) -
Yangyong Zhu,
F. Cutu
Publication year - 2010
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/3.9.839
Subject(s) - template , face (sociological concept) , face detection , computer vision , artificial intelligence , computer science , pattern recognition (psychology) , facial recognition system , programming language , philosophy , linguistics
Face detection is the first important step in many face image processing applications. Although a lot of work has been done on detecting frontal faces much less effort has been put into detecting faces with large image-plane or depth rotations. Most templates used in face detection are whole-face templates. However, such templates are ineffective for faces significantly rotated in depth. We propose to use half-face templates to detect faces with large depth rotations. Our experimental results show that half-face templates significantly outperform whole-face templates in detecting faces having large out-plane rotations and performs as well as whole -face templates in detecting frontal faces.
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