Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding faces in cluttered scenes using random labeled graph matching
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Classification of Unattended and Stolen Objects in Video-Surveillance System
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
A survey of skin-color modeling and detection methods
Pattern Recognition
Intelligent Vehicle Counting Method Based on Blob Analysis in Traffic Surveillance
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
Face Detection in Color Images Using AdaBoost Algorithm Based on Skin Color Information
WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
Face detection and tracking using a Boosted Adaptive Particle Filter
Journal of Visual Communication and Image Representation
Moving object detection in the H.264/AVC compressed domain for video surveillance applications
Journal of Visual Communication and Image Representation
Neural Computing and Applications
Kernel optimization-based discriminant analysis for face recognition
Neural Computing and Applications
People Counting Using Multi-Mode Multi-Target Tracking Scheme
IIH-MSP '09 Proceedings of the 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Facial expression recognition using constructive feedforward neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
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This paper develops a face detection method in color images using a multi-layer Neural Network classification. The proposed method is based on two image processing steps which first detect skin regions in the color image and then extract face information from those regions. Instead of performing huge search in every part of the test images, a pre-processing method for candidate face regions guides the image search using neural networks. The new algorithms perform fast and accurate face detection. Experiments have been carried out and satisfactory results have been obtained which indicate the robustness of the first process to detect faces under different environmental conditions.