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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qing Zhang Bo Fu Mao Ye Ruigang Yang |
| Copyright Year | 2014 |
| Description | Author affiliation: Univ. of Kentucky, Lexington, KY, USA (Qing Zhang; Bo Fu; Mao Ye; Ruigang Yang) |
| Abstract | In this paper we present a novel autonomous pipeline to build a personalized parametric model (pose-driven avatar) using a single depth sensor. Our method first captures a few high-quality scans of the user rotating herself at multiple poses from different views. We fit each incomplete scan using template fitting techniques with a generic human template, and register all scans to every pose using global consistency constraints. After registration, these watertight models with different poses are used to train a parametric model in a fashion similar to the SCAPE method. Once the parametric model is built, it can be used as an animitable avatar or more interestingly synthesizing dynamic 3D models from single-view depth videos. Experimental results demonstrate the effectiveness of our system to produce dynamic models. |
| Starting Page | 676 |
| Ending Page | 683 |
| File Size | 1179962 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479951185 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2014.92 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-23 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Three-dimensional displays Solid modeling Registers Shape Iterative closest point algorithm Joints Cameras Mesh Registration 3D Model Avatar Template Fitting SCAPE |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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