Browsing by Author "Lo, Yung-Sheng"

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Feature-point driven 3D expression editing
(2007)
Chuang, Chii-Yuan
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Lin, I-Chen
;
Lo, Yung-Sheng
;
Lin, Chao-Chih
;
資訊工程學系
Producing a life-like 3D facial expression is usually a labor-intensive process. in movie and game industries, motion capture and 3D scanning techniques, acquiring motion data from real persons, are used to speed up the production. However, acquiring dynamic and subtle details, such as wrinkles, on a face are still difficult or expensive. In this paper, we propose a feature-point-driven approach to synthesize novel expressions with details. Our work can be divided into two main parts: acquisition of 3D facial details and expression synthesis. 3D facial details are estimated from sample images by a shape-from-shading technique. While employing relation between specific feature points and facial surfaces in prototype images, our system provides an intuitive editing tool to synthesize 3D geometry and corresponding 2D textures or 3D detailed normals of novel expressions. Besides expression editing, the proposed method can also be extended to enhance existing motion capture data with facial details.
Image-based detail reconstruction of non-Lambertian surfaces
(2010-01-01)
Lin, I-Chen
;
Chang, Wen-Hsing
;
Lo, Yung-Sheng
;
Peng, Jen-Yu
;
Lin, Chan-Yu
This paper presents a novel optimization framework for estimating the static or dynamic surfaces with details. The proposed method uses dense depths from a structured-light system or sparse ones from motion capture as the initial positions, and exploits non-Lambertian reflectance models to approximate surface reflectance. Multi-stage shape-from-shading (SFS) is then applied to optimize both shape geometry and reflectance properties. Because this method uses non-Lambertian properties, it can compensate for triangulation reconstruction errors caused by view-dependent reflections. This approach can also estimate detailed undulations on text-tireless regions, and employs spatial-temporal constraints for reliably tracking time-varying surfaces. Experiment results demonstrate that accurate and detailed 3D surfaces can be reconstructed from images acquired by off-the-shelf devices. Copyright (C) 2010 John Wiley & Sons, Ltd.