Face Recognition based on Accelerated Joint Boosting and Illumination Normalized Local Gabor Binary Pattern Histogram Sequence

摘要：

Determining what features are optimal for face representation is quite a challenge in Face Recognition. Joint Boosting is a strong algorithm to select important features from feature pool. And, it outperforms other feature selection methods. But it takes quite a long time to train on a large training set. In this paper, an Accelerated Joint Boosting is proposed to resolve the time wasting problem. The contributions of this paper are: (1) We propose an Accelerated Joint Boosting method for feature selection in Face Recognition. (2) An efficient preprocessing chain for Illumination Normalization which is called ‘PP and Histogram Sequence of Local Gabor Binary Pattern (LGBPHS) are combined for robust Face Recognition, and it gets remarkable performance in Face Recognition Grand Challenge version 2.0 experiment 4 (FRGC) 7.

作者: Chengxiong Ruan Qiuqi Ruan Xiaoli Li

作者单位: Institute of Information Science, Beijing Jiaotong University, Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1370-1373

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）