High-resolution animation of facial dynamics-猫眼课题宝

DOI：

10.1049/cp:20070033

发表时间：

2007

期刊：

影响因子：

通讯作者：

中科院分区：

其他

文献类型：

作者：

N. Nadtoka;J. Tena;A. Hilton;James D. Edge

本文提出了一个基于性能的动画和重定向的高分辨率人脸模型从运动捕捉的框架。介绍了一种新的方法，用于学习稀疏的3D运动捕捉标记和密集的高分辨率3D扫描的面部形状和外观之间的映射。一个高分辨率的面部表情空间是从一组3D人脸扫描作为一个人特定的变形模型。在运动捕捉标记位置处采样的稀疏3D人脸点用于构建对应的低分辨率表情空间以表示来自运动捕捉的面部动态。径向基函数插值用于自动映射到高分辨率的面部表情空间的面部动态的低分辨率运动捕捉。这将产生具有真实的面部动态的详细形状和外观的高分辨率面部动画。引入重定向以将面部表情转移到从单张照片或3D扫描捕获的新主题。基于面部形状的解剖学差异将对象特定的高分辨率表情空间映射到新对象。结果面部动画和重定向演示了逼真的动画表情从运动捕捉。

This paper presents a framework for performance-based animation and retargeting of high-resolution face models from motion capture. A novel method is introduced for learning a mapping between sparse 3D motion capture markers and dense high-resolution 3D scans of face shape and appearance. A high-resolution facial expression space is learnt from a set of 3D face scans as a person specific morphable model. Sparse 3D face points sampled at the motion capture marker positions are used to build a corresponding low-resolution expression space to represent the facial dynamics from motion capture. Radial basis function interpolation is used to automatically map the low-resolution motion capture of facial dynamics to the high-resolution facial expression space. This produces a high-resolution facial animation with the detailed shape and appearance of real facial dynamics. Retargeting is introduced to transfer facial expressions to a novel subject captured from a single photograph or 3D scan. The subject specific high- resolution expression space is mapped to the novel subject based on anatomical differences in face shape. Results facial animation and retargeting demonstrate realistic animation of expressions from motion capture.

High-resolution animation of facial dynamics

文献摘要

相似文献