TY - GEN
T1 - Automatic pose-normalized 3D face modeling and recognition systems
AU - Yu, Sunjin
AU - Choi, Kwontaeg
AU - Lee, Sangyoun
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Pose-variation factors present a big problem in 2D face recognition. To solve this problem, we designed a 3D face acquisition system which was able to generate multi-view images. However, this created another pose-estimation problem in terms of normalizing the 3D face data. This paper presents an automatic pose-normalized 3D face data acquisition method that is able to perform both 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with the AAM (Active Appearance Model) and 3D information with a 3D normal vector. The proposed system is based on stereo vision and a structured light system which consists of 2 cameras and 1 projector. In orsder to verify the performance of the proposed method, we designed an experiment for 2.5D face recognition. Experimental results showed that the proposed method is robust against pose variation.
AB - Pose-variation factors present a big problem in 2D face recognition. To solve this problem, we designed a 3D face acquisition system which was able to generate multi-view images. However, this created another pose-estimation problem in terms of normalizing the 3D face data. This paper presents an automatic pose-normalized 3D face data acquisition method that is able to perform both 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with the AAM (Active Appearance Model) and 3D information with a 3D normal vector. The proposed system is based on stereo vision and a structured light system which consists of 2 cameras and 1 projector. In orsder to verify the performance of the proposed method, we designed an experiment for 2.5D face recognition. Experimental results showed that the proposed method is robust against pose variation.
UR - http://www.scopus.com/inward/record.url?scp=70350263656&partnerID=8YFLogxK
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U2 - 10.1007/11949534-65
DO - 10.1007/11949534-65
M3 - Conference contribution
AN - SCOPUS:70350263656
SN - 354068297X
SN - 9783540682974
VL - 4319 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 652
EP - 661
BT - Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings
T2 - 1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006
Y2 - 10 December 2006 through 13 December 2006
ER -