Abstract
In this paper we present an environment for the tracking of a human face obtained from a real video sequence. We will describe the system and discuss the advantages and disadvantages of our approximation. We mainly focus on the situation of the main attributes of the human face (eyes, eyebrows, nose and moth). The tracking algorithm and the ulterior animation of the synthetic model must guarantee the real time response without the need of any additional markup of the actor. Due to the complexity of the process, we make an initial selection of the facial attributes involved without any efficiency or robustness loss. We define a probabilistic model of skin face area and we would like to track this region in the sequence of images. In parallel we propose additional criteria to search inside this tracked area main features in human face (as lisp, eyes, eyebrows, nose, etc..). The tracking algorithm is based in a efficient implementation of continuously adaptive mean shift procedure (CAMSHIFT) and this process is improved also with the second step with feature detections. In this paper only we present the whole process, the tracking background criteria and lips detection procedure. The synthesis phase is out scope of this paper and we generate the facial animations parameters (FAP) as input to a compliant MPEG-4 facial animation engine (FAE). This system is designed as a computer interface for controlling commercial computer applications which include avatar or clones in real time.
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References
Computer Vision Face Tracking for Use in a Perceptual User Interface. Gary R. Bradsky. Microcomputer Research Lab, Intel Corporation (2001); Robust object location detection – Automatic head contour detection. Multimedia communications research laboratory. Bell Labs (2000); Rapid Design of MPEG- 4 Compliant Animated Faces and Bodies. Erich Haratsch.Technical University of Munich (1997); Intel © Image Processing Library & Open Source Computer Vision Library. Reference Manuals. Intel Corporation (2001); ISO/IEC JTC1/WG11 N1902.Text for CD 14496-2 Visual Fribourg meeting (November1997)
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© 2003 Springer-Verlag Berlin Heidelberg
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Perales, F.J., Mas, R., Mascaró, M., Palmer, P., Igelmo, A., Ramírez, A. (2003). A Colour Tracking Procedure for Low-Cost Face Desktop Applications. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_85
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DOI: https://doi.org/10.1007/978-3-540-44871-6_85
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