DocumentCode :
2964136
Title :
Pose invariant face recognition with 3D morphable model and neural network
Author :
Choi, Hyun-Chul ; Kim, Sam-Yong ; Oh, Sang-Hoon ; Oh, Se-young ; Cho, Sun-Young
Author_Institution :
Dept. of Electron. & Electr. Eng., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang
fYear :
2008
fDate :
1-8 June 2008
Firstpage :
4131
Lastpage :
4136
Abstract :
This paper introduces a pose invariant face recognition method with a training image and a query image using 3D morphable model and neural network. Our system uses 3D morphable model to get the reconstructed 3D face from the training image and obtains 2D image patches of facial components from the 3D face under varying head pose. The 2D image patches are used to train a neural network for pose invariant face recognition. Because those patches are obtained from the varying head pose, the neural network has robustness in the query image under the different head pose form the training image. Our pose invariant face recognition system has the performance of correct recognition higher than 98% with BJUT 3D scan database.
Keywords :
face recognition; image reconstruction; learning (artificial intelligence); neural nets; 3D face reconstruction; 3D morphable model; 3D scan database; neural network; pose invariant face recognition; query image; Face detection; Face recognition; Humans; Image databases; Lighting; Magnetic heads; Neural networks; Robustness; Shape; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2008.4634393
Filename :
4634393
Link To Document :
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