Title :
3D Face Recognition Using Multi-level Multi-feature Fusion
Author :
Zhang, Cuicui ; Uchimura, Keiichi ; Caiming Zhang ; Koutaki, Gou
Author_Institution :
Dept. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Abstract :
This paper proposed a novel 3D face recognition algorithm using multi-level multi-feature fusions. A new face representation method named average edge image is proposed in addition to traditional ones such as maximal principal curvature image and range image. In the matching process stage, a new weight calculation algorithm based on the sum rule is presented for feature fusion and match score fusion in order to improve the matching precision. Depending on the complementary characteristic of feature fusion and match score fusion, a combination of them named two-level fusion is proposed. Experiments are conducted using our own 3D database consisting of nearly 400 samples. Mesh simplification is utilized for data reduction. Recognition results show that the new weight calculation method improves the recognition accuracy and the two-level fusion algorithm performs better than feature fusion and match score fusion.
Keywords :
data reduction; face recognition; image fusion; image matching; image representation; mesh generation; solid modelling; 3D database; 3D face recognition algorithm; average edge image; data reduction; face representation method; match score fusion; matching precision; multilevel multifeature fusions; sum rule; two-level fusion; weight calculation algorithm; Face; Face recognition; Feature extraction; Image edge detection; Principal component analysis; Three dimensional displays; 3D face recognition; feature fusion; match score fusion; muliti-level multi-feature fusion; two-level fusion;
Conference_Titel :
Image and Video Technology (PSIVT), 2010 Fourth Pacific-Rim Symposium on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-8890-2
DOI :
10.1109/PSIVT.2010.11