Computer modeling, analysis, and synthesis of dressed humans

We present computer vision techniques for building dressed human models using images. We develop an algorithm for three-dimensional body reconstruction and texture mapping using contour, stereo, and texture information from several images and deformable superquadrics as the model parts. We demonstrate a novel vision technique for analysis of cloth draping behavior. This technique allows for estimation of cloth model parameters, such as bending properties, but can also be used to estimate the contact points between the body and clothing in the range data of dressed humans. Combined with our body reconstruction algorithm and additional constraints on the articulation model, the detection of the garment-body contact points allows construction of a dressed human model in which even the geometry that was covered by clothing in the available data is reasonably well estimated.

[1]  Richard L. Grimsdale,et al.  Computer graphics techniques for modeling cloth , 1996, IEEE Computer Graphics and Applications.

[2]  Richard L. Grimsdale,et al.  A system for modelling and visualization of cloth material , 1995, Comput. Graph..

[3]  G. Borgefors.  Distance transformations in arbitrary dimensions , 1984 .

[4]  Ioannis Athanassiou Kakadiaris.  Motion-based part segmentation, shape and motion estimation of multi-part objects , 1997 .

[5]  Billie J. Collier,et al.  Drape Prediction by Means of Finite-element Analysis , 1991 .

[6]  Nebojsa Jojic,et al.  On Analysis of Cloth Drape Range Data , 1998, ACCV.

[7]  Dimitris N. Metaxas,et al.  Dynamic 3D models with local and global deformations: deformable superquadrics , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[8]  Demetri Terzopoulos,et al.  Constraints on Deformable Models: Recovering 3D Shape and Nonrigid Motion , 1988, Artif. Intell..

[9]  David E. Breen,et al.  Predicting the drape of woven cloth using interacting particles , 1994, SIGGRAPH.

[10]  Daniel Thalmann,et al.  Dressing animated synthetic actors with complex deformable clothes , 1992, SIGGRAPH.

[11]  Dimitris N. Metaxas,et al.  Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Robert C. Bolles,et al.  Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching , 1977, IJCAI.

[13]  Yuan-Fang Wang,et al.  Integration of active and passive sensing techniques for representing three-dimensional objects , 1989, IEEE Trans. Robotics Autom..

[14]  John C. Platt,et al.  Elastically deformable models , 1987, SIGGRAPH.

[15]  Dimitris N. Metaxas,et al.  Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Wolfgang Straßer,et al.  A fast, flexible, particle-system model for cloth draping , 1996, IEEE Computer Graphics and Applications.

[17]  Ioannis A. Kakadiaris,et al.  Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Helen C. Shen,et al.  Computer modeling, analysis and synthesis of dressed humans , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).