[1]林琴,李卫军,董肖莉,等.基于双目视觉的人脸三维重建[J].智能系统学报,2018,13(04):534-542.[doi:10.11992/tis.201701020]
 LIN Qin,LI Weijun,DONG Xiaoli,et al.Face reconstruction based on binocular stereo vision[J].CAAI Transactions on Intelligent Systems,2018,13(04):534-542.[doi:10.11992/tis.201701020]
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年04期
页码:
534-542
栏目:
出版日期:
2018-07-05

文章信息/Info

Title:
Face reconstruction based on binocular stereo vision
作者:
林琴123 李卫军123 董肖莉123 宁欣123 陈鹏123
1. 中国科学院半导体研究所 高速电路与神经网络实验室, 北京 100083;
2. 中国科学院大学 电子学院, 北京 100029;
3. 认知计算技术威富联合实验室, 北京 100083
Author(s):
LIN Qin123 LI Weijun123 DONG Xiaoli123 NING Xin123 CHEN Peng123
1. Laboratory of Artificial Neural Networks and High-peed Circuits, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China;
2. School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100029, China;
3. Cognitive Computing Technology Wei Fu Joint Lab, Beijing 100083, China
关键词:
人脸拓扑结构立体匹配线性插值稠密视差
Keywords:
facial topological informationstereo matchinglinear interpolationdense correspondence
分类号:
TP391
DOI:
10.11992/tis.201701020
摘要:
基于双目立体匹配算法PatchMatch算法,提出了一种获取人脸三维点云的算法。该算法对局部立体匹配算法PatchMatch进行了优化。该方法既不需要昂贵的设备,也不需要通用的人脸三维模型,而是结合了人脸的拓扑结构信息以及立体视觉局部优化算法。此方法采用非接触式的双目视觉采集技术获取左右视角的人脸图像,利用回归树集合(ensemble of regression trees,ERT)算法对人脸图像进行关键点定位,恢复人脸稀疏的视差估计,运用线性插值方法初步估计脸部的稠密视差值,并结合局部立体匹配算法对得到的视差结果进行平滑处理,重建人脸的三维点云信息。实验结果表明,这种算法能够还原出光滑的稠密人脸三维点云信息,在人脸Bosphorus数据库上取得了更加准确的人脸重建结果。
Abstract:
In this paper, we propose a binocular stereo algorithm called PatchMatch for generating a 3D dense point cloud of the human face. The proposed algorithm optimizes a local stereo matching method, also known as PatchMatch, which combines topological information of the human face with a local optimization algorithm for stereo vision and requires neither expensive equipment nor generic face models. With this method, by applying a non-contact binocular vision selection technology, face images at both left and right visual angles are obtained. We use an ensemble of regression trees (ERT) algorithm to position key points of a face image and estimate the sparse disparity of facial landmarks. Then, we use a linear interpolation method to make a preliminarily estimation of the dense facial disparity, and by using the local stereo matching algorithm, we can smooth the obtained visual disparity results and use the three-dimensional point cloud information to rebuild the human face. The experimental results with the Bosphorus database show that the proposed algorithm can recover dense facial three-dimensional point cloud information and obtain more accurate face reconstruction results than other methods on Bosphorus database.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2017-01-22。
基金项目:国家自然科学基金项目(90920013);国家公派留学基金项目(201404910237).
作者简介:林琴,女,1992年生,硕士研究生,主要研究方向为图像处理、模式识别、计算机视觉;李卫军,男,1975年生,研究员,博士,主要研究方向为仿生图像处理技术、仿生模式识别理论与方法、近红外光谱定性分析技术、高维信息计算。发表学术论文30余篇;董肖莉,女,1985年生,助理研究员,主要研究方向为图像处理、模式识别及智能信息处理。
通讯作者:李卫军.E-mail:wjli@semi.ac.cn
更新日期/Last Update: 2018-08-25