Abstract
Face occurrence verification is mandatory stage for color based face detection systems. Facial features extraction using Haar cascades is one of the possible way to classify regions as faces. The purpose of this paper is to provide novel and valuable comparison of two approaches for using Haar cascades in face occurrence verification stage. Performance and accuracy tests have been carried out to decide which of approaches described in the article is more suitable. Results might be crucial while implementing similar face detection system based on skin detection and facial features localization.
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References
Campadelli, P., Lanzarotti, R., Lipori, G.: Automatic facial feature extraction for face recognition. In: Face Recognition, pp. 31–58. I-Tech Education and Publishing (2007)
Chen, Y., Lin, Y.: Simple face-detection algorithm based on minimum facial features. In: IECON 2007, 33rd Annual Conference of the IEEE, Taipei, pp. 455–460. Industrial Electronics Society (November 2007)
Garcia, C., Tziritas, G.: Face detection using quantized skin color regions merging and wavelet packet analysis. IEEE Transactions on Multimedia 1(3), 264–277 (1999)
Gunduz, A., Krim, H.: Facial feature extraction using topological methods. In: Proceedings of Image Processing, ICIP 2003, vol. 1, pp. 673–676 (September 2003)
Hadid, A., Pietikainen, M., Martinkauppi, B.: Color-based face detection using skin locus model and hierarchical filtering. In: Proceedings of 16th International Conference Pattern Recognition, vol. 4, pp. 196–200 (2002)
Hassan, M., Osman, I., Yahia, M.: Walsh-hadamard transform for facial feature extraction in face recognition (2007)
Kam-art, R., Raicharoen, T., Khera, V.: Face recognition using feature extraction based on descriptive statistics of a face image. In: 2009 International Conference on Machine Learning and Cybernetics, Baoding, vol. 1, pp. 193–197 (July 2009)
Mostafa, L., Abdelazeem, S.: Face detection based on skin color using neural networks. In: GVIP 2005 Conference, Cairo, Egypt (December 2005), CICC
Open Source Library of Scientific Tools (March 03, 2011), http://www.scipy.org/
Jones, M., Viola, P.: Rapid object detection using boosted cascade of simple features. In: Computer Vision and Pattern Recognition, vol. (I), pp. 511–518 (2001)
Jones, M., Viola, P.: Robust real-time object detection. In: Second International Workshop on Statistical and Computational Theories of Vision - Modeling, Learning, Computing and Sampling, Vancouver, Canada (July 2001)
Sandeep, K., Rajagopalan, A.N.: Human face detection in cluttered color images using skin color and edge information
Singh, S., Chauhan, D.S., Vatsa, M., Singh, R.: A robust skin color based face detection algorithm, tamkang. Journal of Science and Engineering 6(4), 227–234 (2003)
Sobottka, K., Pitas, I.: Segmentation and tracking of faces in color images. In: Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp. 236–241 (October 1996)
Open source computer vision library (March 03, 2011), http://opencv.willowgarage.com
Vezhnevets, V., Sazonov, V., Andreeva, A.: A survey on pixel-based skin color detection techniques. In: PROC. GRAPHICON 2003, pp. 85–92 (2003)
Schapire, R.E., Freund, Y.: A decision-theoretic generalization of on-line learning and an application to boosting. In: Vitányi, P.M.B. (ed.) EuroCOLT 1995. LNCS, vol. 904, pp. 23–37. Springer, Heidelberg (1995)
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Boryło, P., Matiolański, A., Orzechowski, T.M. (2011). Face Occurrence Verification Using Haar Cascades - Comparison of Two Approaches. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2011. Communications in Computer and Information Science, vol 149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21512-4_36
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DOI: https://doi.org/10.1007/978-3-642-21512-4_36
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