关键词: 人眼检测, 显著极值, PCA验证, 邻域运算

Abstract:

We propose a novel and efficient hierarchical scheme, which can locate the accurate positions of the eyes from frontal face images. First, Gabor transform is used to calculate the salient map and a number of rectangular regions with the maximum saliency values are selected as the coarse eye region candidates for further verification. Second, the two eye windows with the minimum PCA(Principal Component Analysis) reconstruction errors among the eyecandidate regions are selected. Finally, the pupil centers are localized by applying two neighborhood operators within the eye windows. The proposed algorithm is non-iterative, computationally simple and robust to different facial expressions. Experimental results on JAFFE database show that this algorithm can make the detection accuracy of 99.6%, and can achieve a superior performance compared to other state of the art methods.

Key words: eyes detection, saliency values, principal component analysis(PCA)based verification, neighborhood operators