In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
In building a face recognition system for real-life scenarios, one usually faces the problem that is the selection of a feature-space and preprocessing methods such as alignment u...
In this paper we propose a domain partitioning RankBoost approach for face recognition. This method uses Local Gabor Binary Pattern Histogram (LGBPH) features for face representat...
In this paper, a face pose estimation method and its application in video shot selection for face image preprocessing is introduced. The pose estimator is learned by a boosting re...
Bo Wu, Haizhou Ai, Lianhong Cai, Shihong Lao, Zhig...
While existing face recognition systems based on local features are robust to issues such as misalignment, they can exhibit accuracy degradation when comparing images of differing...