Probabilistic Visual Learning for Object Representation
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
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
Face Detection Using Mixtures of Linear Subspaces
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Robust Face Detection at Video Frame Rate Based on Edge Orientation Features
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
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We present an effective method of face and facial feature detection under pose variation in cluttered background. Our approach is flexible to both color and gray facial images and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of neighborhood area of facial features, a new directional template for the facial feature is defined. By applying this template to the input facial image, novel edge-like blob map (EBM) with multiple strength intensity is constructed. And we propose an effective pose estimator using fuzzy logic and a simple PCA method. Combining these methods, robust face localization is achieved for face recognition in mobile robots. Experimental results using various color and gray images prove accuracy and usefulness of the proposed algorithm. This research was supported by Korea Ministry of Science and Technology under the National Research Laboratory project, by Korea Ministry of Education under the BK21 project, and by Korean Ministry of Information and Communication under HNRC-ITRC program at Chung-Ang university supervised by IITA.