Automatic approach to mapping a lifelike 2.5D human face

Abstract An automatic approach to making human face models is proposed. It is a separate system with the input in the form of a range data set and a colour image of a human face. These two sources are processed individually to derive the information necessary to automatically synthesize a lifelike facial model. The information obtained from the facial range data set includes the anatomical sites of features and the geometrical data of the face. The information extracted from the facial colour image is the boundaries of facial features and the attributes of facial textures. These two sources are integrated to produce a volumetric facial model.

[1]  Thomas K. Pilgram,et al.  Facial surface scanner , 1991, IEEE Computer Graphics and Applications.

[2]  N. Dyn,et al.  A butterfly subdivision scheme for surface interpolation with tension control , 1990, TOGS.

[3]  K. Sato,et al.  Range imaging system utilizing nematic liquid crystal mask , 1987 .

[4]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Toru Abe,et al.  Automatic identification of human faces by 3-d shape of surfaces-using vertices of b-spline surface , 1991, Systems and Computers in Japan.

[6]  Jake K. Aggarwal,et al.  Segmentation of chromatic images , 1981, Pattern Recognit..

[7]  Hsien-Che Lee,et al.  Chromatic edge detection: Idealization and reality , 1990, Int. J. Imaging Syst. Technol..

[8]  Parke,et al.  Parameterized Models for Facial Animation , 1982, IEEE Computer Graphics and Applications.

[9]  Hiroshi Harashima,et al.  A facial motion synthesis for intelligent man-machine interface , 1991, Systems and Computers in Japan.

[10]  A. Yuille.  Deformable Templates for Face Recognition , 1991, Journal of Cognitive Neuroscience.

[11]  N. Magnenat-Thalmann,et al.  An Integrated Control View of Synthetic Actors , 1989 .

[12]  Michael Zyda,et al.  Simplification of objects rendered by polygonal approximations , 1991, Comput. Graph..

[13]  Ioannis Andreadis,et al.  Image pixel classification by chromaticity analysis , 1990, Pattern Recognit. Lett..

[14]  Edward R. Dougherty,et al.  Morphological methods in image and signal processing , 1988 .

[15]  Thomas O. Binford,et al.  On Detecting Edges , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Koji Komatsu.  3-D shape reconstruction of human face from a 2-d facial image and provision for change of expression , 1991, Systems and Computers in Japan.

[17]  James S. Duncan,et al.  Parametrically deformable contour models , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Ian H. Witten,et al.  A Methodology for Direct Manipulation of Polygon Meshes , 1989 .

[19]  Alex Pentland,et al.  Automatic lipreading by optical-flow analysis , 1989 .

[20]  Donald P. Greenberg.  More accurate simulations at faster rates (graphics) , 1991, IEEE Computer Graphics and Applications.

[21]  Keith Waters,et al.  A muscle model for animation three-dimensional facial expression , 1987, SIGGRAPH.