Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Genetic Feature Subset Selection for Gender Classification: A Comparison Study
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Visual surface segmentation from stereo
Image and Vision Computing
Face segmentation using skin-color map in videophone applications
IEEE Transactions on Circuits and Systems for Video Technology
Subjective evaluation of stereoscopic images: effects of camera parameters and display duration
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
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In this paper we propose a new range-based face recognition for significant improvement in the recognition rate using an optimized stereo acquisition system. The optimized 3D acquisition system consists of an eyes detection algorithm, facial pose direction distinction, and principal component analysis (PCA). The proposed method is carried out in the YCbCr color space in order to detect the face candidate area. To detect the correct face, it acquires the correct distance of the face candidate area and depth information of eyes and mouth. After scaling, the system transfers the pose change according to the distance. The face is finally recognized by the optimized PCA for each area with the facial pose elements detected. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.