By Abdenour Hadid, Matti Pietikäinen, Stan Z. Li (auth.), S. Kevin Zhou, Wenyi Zhao, Xiaoou Tang, Shaogang Gong (eds.)
The 2007 IEEE overseas Workshop on research and Modeling of Faces and Gestures(AMFG)isthethirdworkshopofitstypeorganizedinconjunctionwith ICCV, this time in Rio de Janeiro, Brazil. Our basic target is to compile researchersand study groupsto assessment the prestige of popularity, research and modeling of face, gesture, task, and behaviour; to debate the demanding situations that we face; and to discover destiny instructions. This yr we got fifty five submissions. every one paper used to be reviewed by way of 3 software committee participants. the full reviewing procedure was once double blind. However,due to measurement restrict, we have been basically capable of accommodate 22 papers, between which eight are orals and 14 are posters. the themes lined by means of those authorised papers contain function illustration, 3D face, powerful acceptance lower than pose and illumination variations,video-basedface recognition,learning,facial movement research, physique pose estimation, and signal popularity. a unique be aware of thank you is going to Dr. Feng Zhao, our organizing chair, for his commitment and nice e?orts in preserving either the net submission procedure and workshop web site and in dealing with many of the writer contacts. we're indebted to the advisory committee individuals for his or her invaluable feedback and to this system committee contributors for his or her labor and well timed studies. ultimately, we thank Cognitec procedure GmbH and Siemens company learn for his or her sponsorship. October 2007 S. Kevin Zhou Wen-Yi Zhao Xiaoou Tang Shaogang Gong association AMFG 2007 was once held along side ICCV 2007. Workshop Chairs S. Kevin Zhou Siemens company examine Wen-Yi Zhao Intuitive Surgical, Inc.
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Additional info for Analysis and Modeling of Faces and Gestures: Third International Workshop, AMFG 2007 Rio de Janeiro, Brazil, October 20, 2007 Proceedings
The texture model provides one way of ensuring proper alignment of features (eyes, eyebrows, lips, etc) in the fitted model. Another possible approach to achieve alignment, and one we plan to explore in the future, is to use only shape in the stereo fitting process and to incorporate a stereo matching term that is more sophisticated than simple per-vertex intensity differences. This is the approach taken in , for example, where window-based matching is employed. g. ), as well as better models for the distribution of the error in the modeling of texture (Eq.
The rest of the paper is arranged as follows: The HPCA algorithm is described in section 2; In section 3, we present results from HPCA; section 4 describes the SFS method; section 5 presents SFS results; section 6 concludes the paper. 2 Hybrid Principle Component Analysis In this section, we describe the HPCA algorithm. To perform the HPCA algorithm, we need a set of M training images. Each image is a hybrid composed of 48 Q. Wu and J. Ben-Arie a 2D [n × m] gray scale image and a corresponding [n × m] range image.
Throughout this section, we refer to these as stereo+ texture, stereo, robust stereo+texture, and robust stereo, respectively. To ensure a valid comparison between the different cases, we used equivalent parameters for the feature match weight (λ ) and the model priors (σs and σt ) in each experiment. Only the first 40 shape and texture basis vectors were used, since this was found to provide adequate results. U. Leuven stereo face database , which contains stereo pairs of each individual in eight different positions.