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首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2006) pt.1; 20060508-11; Glasgow(GB) >Image-Based 3D Face Modeling from Stereo Images
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Image-Based 3D Face Modeling from Stereo Images

机译：立体图像中基于图像的3D人脸建模

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摘要

This paper presents an automatic and novel method to generate a realistic 3D face model from stereo images. Typically, an image-based 3D face modeling system is in need of human intervention in facial feature extraction stage. To remove this human intervention, we propose HT(Hue-Tint) skin color model for facial feature extraction. Based on the proposed chrominance model, we can detect facial region and extract facial feature positions. Subsequently, the facial features are adjusted by using edge information of the detected facial region along with the proportions of the face. Moreover, the proposed facial extraction method can effectively eliminate the epipolar constraints caused by using stereo vision approach. In order to produce a realistic 3D face model, we adopt RBF(Radial-Based Function) to deform the generic face model according to the detected facial feature points from stereo images. For deformation locality parameter of RBF is critical since it can have significant impact on the quality of deformation. Thus, we propose new parameter decision rule that is applicable to scattered data interpolation. It makes clusters of feature points to detect points under the influence of each width parameter. From the experiments, we can show the proposed approach efficiently detects facial feature points and produces a realistic 3D face model.
机译：本文提出了一种自动新颖的方法，可以从立体图像生成逼真的3D人脸模型。通常，基于图像的3D面部建模系统在面部特征提取阶段需要人工干预。为了消除这种人工干预，我们提出了HT（Hue-Tint）肤色模型用于面部特征提取。基于提出的色度模型，我们可以检测面部区域并提取面部特征位置。随后，通过使用检测到的面部区域的边缘信息以及面部比例来调整面部特征。此外，提出的人脸提取方法可以有效消除立体视觉方法引起的对极约束。为了产生逼真的3D人脸模型，我们采用RBF（径向功能）根据从立体图像中检测到的人脸特征点使通用人脸模型变形。对于变形，RBF的局部性参数至关重要，因为它会对变形质量产生重大影响。因此，我们提出了适用于分散数据插值的新参数决策规则。它使特征点聚类以在每个宽度参数的影响下检测点。从实验中，我们可以证明所提出的方法可以有效地检测面部特征点并生成逼真的3D面部模型。

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