Abstract
Face detection is a challenging problem having a wide range of security and surveillance-based applications. Skin color can be an important differentiator and used to augment the performance of automatic face detection. However, obtaining skin color consistency across illumination, different camera settings, and diverse ethnicity is a challenging task. Static skin color models that rely on image preprocessing are able to bring only limited consistency. Their performance in terms of accuracy and computation time degrades severely in real-world videos. In this paper, we study the dynamics of different color models on a database of five videos containing more than 93,000 manually annotated face images. Further, we propose an adaptive skin color model to reduce the false accept cases of Adaboost face detector. Since the face color distribution model is regularly updated using previous Adaboost responses, we find the system to be more effective to real-world environmental covariates. Importantly, the adaptive nature of the skin classifier does not significantly affect the computation time.
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Notes
- 1.
We will make the annotated database, an OpenCV implementation of the annotation tool, and proposed algorithm publicly available for the researchers. To maintain anonymity, we have not included download details.
- 2.
The experiments were conducted on Pentium Core 2 Duo, 2.66 GHz with 4 GB RAM in real time.
References
Hou, Y., Peng, Q.: Face detection based on adaboost and skin color. In: International Symposium on Information Science and Engineering, pp. 407–410 (2009)
Kakumanu, P., Makrogiannis, S., Bourbakis, N.: A survey of skin-color modeling and detection methods. Pattern Recognit. 40(3), 1106–1122 (2007)
Preston, S.: The 68–95-99.7 rule for normal distributions. World Wide Web Electronic Publication (2010)
Soriano, M., Martinkauppi, B., Huovinen, S., Laaksonen, M.: Skin detection in video under changing illumination conditions. In: Proceedings of International Conference on Pattern Recognition, vol. 1, pp. 839–842 (2000)
Stern, H., Efros, B.: Adaptive color space switching for face tracking in multi-colored lighting environments. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 249–254 (2002)
Vezhnevets, V., Sazonov, V., Andreeva, A.: A survey on pixel-based skin color detection techniques. In: Proceedings of the Graphicon, pp. 85–92 (2003)
Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57, 137–154 (2004)
Wu, Y.W., Ai, X.: An improvement of face detection using adaboost with color information. In: International Colloquium on Computing, Communication, Control, and Management, pp. 317–321 (2008)
Yang, M.H., Ahuja, N.: Detecting human faces in color images. In: IEEE International Conference on Image Processing, pp. 127–130 (1998)
Zhang, Z., Gunes, H., Piccardi, M.: An accurate algorithm for head detection based on xyz and hsv hair and skin color models. In: IEEE International Conference on Image Processing, pp. 1644–1647 (2008)
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© 2016 Springer India
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Jairath, S., Bharadwaj, S., Vatsa, M., Singh, R. (2016). Adaptive Skin Color Model to Improve Video Face Detection. In: Singh, R., Vatsa, M., Majumdar, A., Kumar, A. (eds) Machine Intelligence and Signal Processing. Advances in Intelligent Systems and Computing, vol 390. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2625-3_12
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DOI: https://doi.org/10.1007/978-81-322-2625-3_12
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