面向互联网图像视频的鲁棒人脸分析与识别技术研究

项目名称： 面向互联网图像视频的鲁棒人脸分析与识别技术研究

项目编号： No.61472410

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 计算机科学学科

项目作者： 汤晓鸥

作者单位： 中国科学院深圳先进技术研究院

项目金额： 86万元

中文摘要： 伴随着移动终端摄像头的普及和移动互联网的发展，互联网上照片视频数量快速增加。如何高效鲁棒的识别网络图像中的人脸已经成为一个亟待解决的问题。网络照片和视频往往在不可控的自然条件下拍摄，姿势、光线、表情和化妆等变化复杂，且人脸图像的分辨率可能很低，这对传统的人脸识别技术带来巨大的挑战。本项目以机器学习为主要工具，从底层特征的学习、复杂条件下人脸的比对和识别算法等多方面展开研究。我们将建立一个大的人脸数据库对算法进行验证。本项目对于推动人脸识别技术在复杂、不可控环境下的广泛应用有着重要的意义。

中文关键词： 人脸识别；机器学习；互联网图像视频；人脸描述子

英文摘要： Along with the popularization of mobile cameras and the evolve of mobile Internet, the number of online photos and invideos increases rapidly. How to conduct efficeint and rubost face recognition in web images has become a vital problem to be solved. Web photos and videos are always taken under unconstrained and natural enviroments. Pose, illumuntation, expression, age and makeup can bring complex variations in face images. Moreover, face image in webs laways has low resolution. Faces these challenges, this project takes machine learning as main tools and conducet ressearchers from several aspects, including, reconstructing canonical view of face images, learning local descriptors, mining high level indentiy features, and developping recognition algorithmns for low resolution images. This project will develop a deep model to learn complex pose and lighting transforms in uncontrolled environment and reconstruct face images in the frontal pose and with neutral illumination (we call it the canonical view) from face photos in the wild. This project will also study recognition algorithm for low resolution and blurred face images. Given the importance of data size in the training of deep models, we also propose to construct a large face database to overcome various limitations of existing datasets. The outcome of this research will advance the technologies of face recognition in complex and uncontrolled environments.

英文关键词： Face recognition;Machine learning;Internet Image and Video;Face descritor