On Selecting an Appropriate Colour Space for Skin Detection
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Machine Vision and Applications - Special issue: IEEE WACV
A face location and recognition system based on tangent distance
Multimodal interface for human-machine communication
Image-based 3D face modeling system
EURASIP Journal on Applied Signal Processing
Detecting skin in face recognition systems: A colour spaces study
Digital Signal Processing
Information Security Tech. Report
New fuzzy skin model for face detection
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
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This paper describes a method for the detection and tracking of human face and facial features. Skin segmentation is learnt from samples of an image. After detecting a moving object , the corresponding area is searched for clusters of pixels with a known distribution. Since we only use the hue (color) component this process is quite insensitive to illumination changes. The face localization procedure looks for areas in the segmented area which resemble a head. Using simple heuristics, the located head is searched and its centroid is fed back to a camera motion control algorithm which tries to keep the face centered in the image using a pan-tilt camera unit. Furthermore the system is capable of tracking, in every frame, the three main features of a human face. Since precise eye location is computationally intensive, an eye and mouth locator using fast morphological and linear filters is developed. This allows for frame-by-frame checking, which reduces the probability of tracking a non basis feature, yielding a higher success ratio. Velocity and robustness are the main advantages of this fast facial feature detector.