Abstract
A system that performs the detection and tracking of a face in real-time in real video sequences is presented in this paper. The face is detected in a complex environment by a model of human colour skin. Very good results are obtained, since the colour segmentation removes almost all the complex background and it is realized to a very high-speed, making the system very robust. On the other hand, fast and stable real-time tracking is then achieved via biometric feature extraction of face using connected components labelling. Tracking does not require a precise initial fit of the model. Therefore, the system is initialised automatically using a very simple 2D face detector based on target ellipsoidal shape. Results are presented showing a significant improvement in detection rates when the whole sequence is used instead of a single image of the face. Experiments in tracking are reported.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Otsu, N.: A Threshold Selection Meted from Gray-Level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9, 62–66 (1979)
Hjelmas, E., Low, B.K.: Face detection: A survey. Computer Vision and Image Understanding 83(3), 236–274 (2001)
Yang, M.-H., Kriegman, D., Ahuja, N.: Detecting faces in images: A survey. Transactions on Pattern Analysis and Machine Intelligence 24(1), 34–58 (2002)
Birchfield, S.: Elliptical head tracking using intensity gradients and color histograms. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 232–237 (1998)
La Cascia, M., Sclaro, S.: Fast, reliable head tracking under varying illumination: An approach based on registration of texture-mapped 3d models. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(4), 322–336 (2000)
Viola, P., Jones, M.J., Snow, D.: Detecting pedestrians using patterns of motion and appearance. In: International Conference on Computer Vision, vol. 2, pp. 734–741 (2003)
Papageorgiou, C., Oren, M., Poggio, T.: A general framework for object detection. In: Proceedings of the International Conference on Computer Vision, pp. 555–562 (1998)
Jones, M.J., Rehg, J.M.: Statistical Color Models with Application to Skin Detection. Tech. Rep. Cambridge Research Laboratory (1998)
Haralick, R.M., Shapiro, L.: Computer and Robot Vision. 1, pp. 28–48. Addison Wesley, Reading (1992)
Hsu, R.L., Abdel-Mottaleb, M., Jain, A.K.: Face detection in color images. IEEE Trans. Pattern Anal. Machine Intell. 24(5), 696–706 (2002)
Chai, D., Bouzerdoum, A.: A Bayesian approach to skin color classification in YCbCr color space. In: IEEE TENCON00, vol. 2, pp. 421–424 (2000)
Wong, K.W., Lam, K.M., Siu, W.C.: A robust scheme for live detection of human faces in color images. Signal Process. Image Commun. 18(2), 103–114 (2003)
Pratt, W.K.: Digital Image Processing, 2nd edn. John Wiley and Sons, Chichester (1991)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Zapata, J., Ruiz, R. (2007). Biometric and Color Features Fusion for Face Detection and Tracking in Natural Video Sequences. In: Mira, J., Álvarez, J.R. (eds) Nature Inspired Problem-Solving Methods in Knowledge Engineering. IWINAC 2007. Lecture Notes in Computer Science, vol 4528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73055-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-540-73055-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73054-5
Online ISBN: 978-3-540-73055-2
eBook Packages: Computer ScienceComputer Science (R0)