Automatic 3D Face Correspondence Based on Feature Extraction in 2D Space

被引：0

作者：

Gong, Xun ^{[1
]}

Cao, Shuai ^{[1
]}

Li, Xinxin ^{[2
]}

Yuan, Ping ^{[1
]}

Zou, Hemin ^{[1
]}

Ye, Chao ^{[1
]}

Guo, Junyu ^{[1
]}

Wang, Chunyao ^{[1
]}

机构：

[1] SW Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 600031, Peoples R China

[2] Sichuan Univ, Jincheng Coll, Chengdu 611731, Peoples R China

来源：

ROUGH SET AND KNOWLEDGE TECHNOLOGY (RSKT) | 2010年 / 6401卷

基金：

中国国家自然科学基金;

关键词：

Dense correspondence; 3D face; re-sampling; MODELS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This present study proposes to solve 3D faces correspondence in 2D space. Texture maps of 3D models are generated at first by unwrapping 3D faces to 2D space. Following this, we build planar templates based on the 2D average shape computed by a group of annotated texture map. In this paper, landmarks on the unwrapped texture images are located automatically and the final correspondence is built according to the templates. Experimental results show that the presented method is stable and can achieve good matching accuracy.

引用

页码：419 / 426

页数：8

共 12 条

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