Explanation-based facial motion tracking using a piecewise Bezier volume deformation model

Hai Tao, Thomas S. Huang
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引用次数: 117

Abstract

Capturing real motions from video sequences is a powerful method for automatic building of facial articulation models. In this paper, we propose an explanation-based facial motion tracking algorithm based on a piecewise Bezier volume deformation model (PBVD). The PBVD is a suitable model both for the synthesis and the analysis of facial images. It is linear and independent of the facial mesh structure. With this model, basic facial movements, or action units, are interactively defined. By changing the magnitudes of these action units, animated facial images are generated. The magnitudes of these action units can also be computed from real video sequences using a model-based tracking algorithm. However, in order to customize the articulation model for a particular face, the predefined PBVD action units need to be adaptively modified. In this paper, we first briefly introduce the PBVD model and its application in facial animation. Then a multiresolution PBVD-based motion tracking algorithm is presented. Finally, we describe an explanation-based tracking algorithm that takes the predefined action units as the initial articulation model and adaptively improves them during the tracking process to obtain a more realistic articulation model. Experimental results on PBVD-based animation, model-based tracking, and explanation-based tracking are shown in this paper.
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基于解释的基于分段贝塞尔体变形模型的面部运动跟踪
从视频序列中捕捉真实动作是自动建立面部关节模型的一种有效方法。本文提出了一种基于分段贝塞尔体积变形模型(PBVD)的基于解释的面部运动跟踪算法。PBVD是一种适合于人脸图像合成和分析的模型。它是线性的,独立于面部网格结构。在这个模型中,基本的面部动作或动作单元是交互式定义的。通过改变这些动作单元的大小,可以生成动画面部图像。这些动作单元的大小也可以使用基于模型的跟踪算法从真实视频序列中计算出来。然而,为了定制特定人脸的关节模型,需要自适应地修改预定义的PBVD动作单元。本文首先简要介绍了PBVD模型及其在人脸动画中的应用。然后提出了一种基于pbvd的多分辨率运动跟踪算法。最后,我们描述了一种基于解释的跟踪算法,该算法将预定义的动作单元作为初始衔接模型,并在跟踪过程中自适应地改进它们,以获得更真实的衔接模型。本文给出了基于pbvd的动画、基于模型的跟踪和基于解释的跟踪的实验结果。
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