非限制环境下人脸识别关键技术研究

项目名称： 非限制环境下人脸识别关键技术研究

项目编号： No.61273270

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 胡海峰

作者单位： 中山大学

项目金额： 80万元

中文摘要： 人脸识别一直是计算机视觉和模式识别领域的研究热点，而非限制环境下的人脸识别，由于姿态、光照的多样性以及图像质量的不可预见性，更富有挑战性，近年来成为新的关注点。围绕这些难题，本项目将展开如下研究：(1)拟研究基于三维模型的多姿态人脸识别技术，重点解决基于单一样本多姿态人脸图像的三维外形重建以及基于多层次描述的三维人脸表征等问题；(2)拟对极端光照变化下的人脸表征方法展开研究，重点解决非朗伯反射约束条件下的光照不变人脸特征提取以及松弛配准条件下的人脸稀疏表示问题；(3)拟对超低分辨率的人脸图像重构进行研究，重点解决多模态非线性关系学习以及基于语义约束的人脸超分辨率重构等问题。通过本课题研究，期望在三维人脸表征、光照不变人脸特征提取以及超低分辨率人脸图像重构等方面获得突破。最后，我们将利用本研究所得的新理论和方法，构建一个面向实际环境的人脸识别系统。

中文关键词： 人脸识别；人脸表征；光照变化；人脸超分辨率技术；深度学习

英文摘要： Face recognition has long been a hot research subject in computer vision and pattern recognition field. Face recognition in unconstrained environments is even more challenging due to the variety and unpredictability of illumination, pose and face image quality. In order to effectively solve the above problems, we will make deep research in this project to obtain the key approach of unconstrained face recognition, which include: (1) Deep research will be made on the 3D-model based face recognition for solving large pose variations. Our work will be concentrated on two problems, i.e. how to generate 3D models from any single 2D images and how to represent 3D face with using multiscale descriptors. (2) Deep research will be made on the face recognition under varying illumination conditions. Our work will be focused on two problems, i.e., how to obtain the illumination-invariant facial features under Non-Lambertian assumption and, how to solve the illumination problem with Sparse Representation under weak image alignment constraint. (3) Deep research will be made on face super-resolution (SR) techniques. We will find a new approach to learn the nonlinear relationship between the high-resolution image space and the very low resolution image space for face SR. Moreover, we will investigate how to introduce the semant

英文关键词： Face Recognition；Face Representation；Illumination Variation；Face Super-resolution；Deep Learning