Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection From Color Images Using a Fuzzy Pattern Matching Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
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
Statistical color models with application to skin detection
International Journal of Computer Vision
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Rule-based face detection in frontal views
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Robust Real-Time Face Detection
International Journal of Computer Vision
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Digital Signal Processing
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This paper proposes real-time face tracking in a multi-subject environment with a pan-tilt-zoom camera using the fuzzy system technique. Tracking is based on detected faces in the Hue-Saturation-Value (HSV) color space. To detect faces, a fuzzy classifier segments skin colors in the HS color space. To reduce the influence of illumination, a fuzzy system is designed to adaptively determine the fuzzy classifier segmentation threshold according the V color space of an image. Detected skin regions are considered face candidates. Shape and color features serve as another fuzzy classifier inputs, leading to a final detection. For face tracking, a Kalman filter algorithm predicts face detection regions and corrects tracking trajectory. When no face is detected, the consecutive frame difference is employed to track the moving person to avoid tracking lost. To track a specific person among multiple persons, a clothing color histogram in the HS space serves as the determination criterion. The performance of the proposed face detection method is compared to other real-time face detection methods. In real-time operations, the tracking system uses camera panning, tilting, and zooming operations to keep the tracked person within the camera view and maintain a suitable face size in the image.