Video-Rate Hair Tracking System Using Kinect

  • Kazumasa Suzuki
  • Haiyuan Wu
  • Qian Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7786)


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.


Hair Tracking Hair Detection Kinect Video-Rate the color and the depth information 


  1. 1.
    Yacoob, Y., Davis, L.S.: Detection and Analysis of Hair. PAMI 28(7) (2006)Google Scholar
  2. 2.
    Lee, K., Anguelov, D., Sumengen, B., Gokturk, S.: Markov random field models for hair and face segmentation. In: FG (2008)Google Scholar
  3. 3.
    Julian, P., Dehais, C., Lauze, F., Charvillat, V., Bartoli, A., Choukroun, A.: Automatic Hair Detection in the Wild. In: ICPR (2010)Google Scholar
  4. 4.
    Oike, H., Wu, H., Wada, T.: Adaptive Selection of Non-Target Cluster Centers for K-means Tracker. In: 19th Int. Conf. on Pattern Recognition (2008)Google Scholar
  5. 5.
    Suzuki, K., Qi, Y., Wu, H.: Tracking Face and Hair using Extended K-means Tracker, MIRU, Demo, pp.1699–1700 (2011)Google Scholar
  6. 6.
    Hua, C., Wu, H., Chen, Q., Wada, T.: K-means tracker: A General Algorithm for Tracking People. Journal of Multimedia 1(4), 46–53 (2006)CrossRefGoogle Scholar
  7. 7.
    Wu, H., Suzuki, K., Wada, T., Chen, Q.: Accelerating Face Detection by Using Depth Information. In: Pacific Rim Symposium on Advances in Image and Video Technology, pp. 657–667 (2009)Google Scholar
  8. 8.
    Viola, P., Jones, M.: Robust Real-Time Face Detection. IJCV 57(2), 137–154 (2004)CrossRefGoogle Scholar
  9. 9.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kazumasa Suzuki
    • 1
  • Haiyuan Wu
    • 1
  • Qian Chen
    • 1
  1. 1.Faculty of Systems EngineeringWakayama UniversityJapan

Personalised recommendations