Abstract
This paper analyses the practical application of the methods for face and head localization in colour images with varying background. The Haar Cascade Classifier and Local Binary Pattern were selected as basic methods because of their high efficiency in this type of applications. The results obtained in the test set of images prompted the authors to choose the Haar Cascade Classifier. This method was then implemented in the face detection module, which is part of a comprehensive system for determining the forbidden regions.
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References
Beigzadeh, M., Mafadoost, M.: Detection of Face and Facial Features in digital Images and Video Frames. In: Cairo International Biomedical Engineering Conference, CIBEC 2008, pp. 1–4 (2008)
Zhang, C., Zhang, Z.: A Survey of Recent Advances in Face Detection. Technical report, Microsoft Research, 577 (2010)
Yang, M., Kriegman, J., Ahuja, N.: Detecting faces in images: A survey. IEEE Transaction on Pattern Analysis and Machine Intelligence 24(1), 34–58 (2002)
Miao, J., Gao, W., Chen, Y., Lu, J.: Gravity-center template based human face feature detection. In: Tan, T., Shi, Y., Gao, W. (eds.) ICMI 2000. LNCS, vol. 1948, pp. 207–214. Springer, Heidelberg (2000)
Hsu, R.L., Abdel-Mottaleb, M., Jain, A.K.: Face detection in color images. IEEE Pattern Analysis and Machine Intelligence 24, 696–706 (2002)
Phung, S.L., Bouzerdoum, A., Chai, D., Kuczborski, W.: A color-based approach to automatic face detection. In: Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, pp. 531–534 (2003)
Lanitis, A., Taylor, C., Cootes, T.F.: An Automatic Face Identification System Using Flexible Appearance Models. Image and Vision Computing 13(5), 392–401 (1995)
Chan, Y.H., Bakar, S.A., Rahman, S.A.: Face Detection System Based on Feature-Based Chrominance Colour Information. In: International Conference on Computer Graphics, Imaging and Visualization, pp. 153–158 (2004)
Mostafa, L., Abdelazeem, S.: Face detection Based on Skin Color using Neural Network. In: GVIP 2005 Conference, Cairo, Egypt, pp. 53–58 (December 2005)
Jo, C.-Y.: Face detection using lbp features. Tech. Rep., Stanford University. CS 229 Final Project Report (December 2008)
Zhang, L., Chu, R., Xiang, S., Liao, S., Li, S.Z.: Face Detection Based on Multi-Block LBP Representation. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 11–18. Springer, Heidelberg (2007)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of 2001 IEEE International Conference on Computer Vision and Pattern Recognition, pp. 511–518 (2001)
Padilla, R., Costa Filho, C.F.F., Costa, M.G.F.: Evaluation of Haar Cascade Classifiers Designed for Face Detection. World Academy of Science, Engineering and Technology 64 (2012)
Ramirez, G.A., Fuentes, O.: Multi-Pose Face Detection with Asymmetric Haar Features. In: IEEE Workshop on Applications of Computer Vision, WACV 2008, pp. 1–6 (2008)
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Marzec, M., Lamża, A., Wróbel, Z., Dziech, A. (2014). Methods for Face Localization in Static Colour Images with an Unknown Background. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2014. Communications in Computer and Information Science, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-319-07569-3_14
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DOI: https://doi.org/10.1007/978-3-319-07569-3_14
Publisher Name: Springer, Cham
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