关键词: 人脸识别, 梯度方向直方图, 主成分分析, 自适应加权, 支持向量机

Abstract: This paper proposes a novel approach for face recognition based on Adaptively Weighted Histograms of Oriented Gradients（AW-HOG）to solve the issues of low face recognition rate in complex environments. Firstly, AW-HOG feature is available by fusing the weighting map and the traditional HOG feature of the sub-images divided from the original whole face images. And the weighting map is adaptively computed on account of the contribution of each sub-image. After that, the dimensions of AW-HOG features are reduced by Principal Component Analysis（PCA）and the final classification features are generated. Finally, Support Vector Machine（SVM）is utilized in face classification and recognition using the final features. Experimental results based on Yale B and AR standard face databases demonstrate that the proposed approach not only obviously enhances face recognition rate in complex environments but also has certain robustness to the influence of light and expression.

Key words: face recognition, Histograms of Oriented Gradients（HOG）, Principal Component Analysis（PCA）, adaptively weighted, Support Vector Machine（SVM）