Automatic extraction of face-features
Pattern Recognition Letters
Detection and localization of faces on digital images
Pattern Recognition Letters
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for tracking human faces based on chromatic histograms
Pattern Recognition Letters
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Focus of Attention for Face and Hand Gesture Recognition Using Multiple Cameras
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Learning-Based Approach to Real Time Tracking and Analysis of Faces
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A procedure for face detection & recognition
MOAS'07 Proceedings of the 18th conference on Proceedings of the 18th IASTED International Conference: modelling and simulation
Robust multipose face detection in images
IEEE Transactions on Circuits and Systems for Video Technology
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Automatic human face detection is considered as the initial process of any fully automatic system that analyzes the information contained in human faces (e.g., identity, gender, expression, age, race and pose). In this paper, color segmentation is used as a first step in the human face detection process followed by grouping likely face regions into clusters of connected pixels. Median filtering is then performed to eliminate the small clusters and the resulting blobs are matched against a face pattern (ellipse) subjected to constraints for rejecting non-face blobs. The system was implemented and validated for images with different formats, sizes, number of people, and complexity of the image background.