Abstract
This paper introduces a novel algorithm named G-HDR, which is a Gabor features based method using Hierarchical Discriminant Regression (HDR) for multiview face recognition. Gabor features help to eliminate the influences to faces such as changes in illumination directions and expressions; Modified HDR tree help to get a more precise classify tree to realize the coarse-to-fine retrieval process. The most challenging things in face recognition are the illumination variation problem and the pose variation problem. The goal of Our G-HDR is to overcome both difficulties. We conducted experiments on the UMIST database and Volker Blanz’s database and got good results.
This work was supported in part by Natural Science Foundation of China under contracts 60003017 and 60373020, China 863 Plans under contracts 2002AA103065, and Shanghai Municipal R&D Foundation under contracts 03DZ15019 and 03DZ14015, MoE R&D Foundation under contracts 104075.
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Yao, D., Xue, X., Guo, Y. (2004). Gabor Features Based Method Using HDR (G-HDR) for Multiview Face Recognition. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds) Advances in Biometric Person Authentication. SINOBIOMETRICS 2004. Lecture Notes in Computer Science, vol 3338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30548-4_22
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DOI: https://doi.org/10.1007/978-3-540-30548-4_22
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