標題: A nonparametric regression model for virtual humans generation
作者: Chou, Yun-Feng
Shih, Zen-Chung
資訊工程學系
Department of Computer Science
關鍵字: Image deformation;Nonparametric regression;Elliptic radial basis functions;Functional approximation;Locally weighted regression
公開日期: 1-三月-2010
摘要: In this paper, we propose a novel nonparametric regression model to generate virtual humans from still images for the applications of next generation environments (NG). This model automatically synthesizes deformed shapes of characters by using kernel regression with elliptic radial basis functions (ERBFs) and locally weighted regression (LOESS). Kernel regression with ERBFs is used for representing the deformed character shapes and creating lively animated talking faces. For preserving patterns within the shapes, LOESS is applied to fit the details with local control. The results show that our method effectively simulates plausible movements for character animation, including body movement simulation, novel views synthesis, and expressive facial animation synchronized with input speech. Therefore, the proposed model is especially suitable for intelligent multimedia applications in virtual humans generation.
URI: http://dx.doi.org/10.1007/s11042-009-0412-7
http://hdl.handle.net/11536/5807
ISSN: 1380-7501
DOI: 10.1007/s11042-009-0412-7
期刊: MULTIMEDIA TOOLS AND APPLICATIONS
Volume: 47
Issue: 1
起始頁: 163
結束頁: 187
顯示於類別:期刊論文


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  1. 000274437400010.pdf