Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
Frontal face authentication using discriminating grids withmorphological feature vectors
IEEE Transactions on Multimedia
A generic approach to simultaneous tracking and verification in video
IEEE Transactions on Image Processing
Modeling phase spectra using gaussian mixture models for human face identification
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
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This paper proposes a novel method for video-based real time face authentication. The proposed method uses motion information to detect the face region, and the face region is processed in YC/sub r/C/sub b/ color space to determine the location of the eyes. The system extracts only the gray level features relative to the location of the eyes. Autoassociative neural network (AANN) model is used to capture the distribution of the extracted gray level features. Experimental results show that the proposed system gives an equal error rate of less than 1% in real time for 25 subjects. The performance of the proposed method is invariant to size and tilt of the face, and is also insensitive to variations in natural lighting conditions.