Robust Real-Time Face Detection
International Journal of Computer Vision
Detection and Analysis of Hair
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accelerating Face Detection by Using Depth Information
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Automatic Hair Detection in the Wild
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
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In this paper, we propose automatic hair detection and tracking system that runs at video-rate (30frame per-second) by making use of both the color and the depth information of the images obtained from a Kinect. Our system has three characteristics: 1) Using a 6D feature vector to describe both the 3D color feature and 3D geometric feature of each pixel uniformly; 2) Classifying pixels in images into foreground (e.g. hair) and background with K-means clustering algorithm; 3) Automatic selecting and updating the cluster centers of foreground and background before and during hair tracking. Our system can track hair of any color or style robustly in clustered background where some objects have color similar to the hair, or in environment where the illumination changes. Moreover, our algorithm can be used for tracking a face (or head) if the face (skin+hair) is selected as foreground.