基于稀疏表达理论和RGBD图像的人脸表情识别

项目名称： 基于稀疏表达理论和RGBD图像的人脸表情识别

项目编号： No.61503410

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 欧阳琰

作者单位： 中国人民解放军空军预警学院

项目金额： 21万元

中文摘要： 当前表情识别领域亟待解决的难点问题之一为如何构建一种能对遮挡、噪声和光照不均等异常情况鲁棒的识别方法。基于稀疏表达理论的分类方法是通过模拟生物视觉系统提出的，前期的研究证明了其对遮挡和噪声具有一定的鲁棒性。本项目拟从RGBD图像中分别提取二维特征和三维特征，并结合基于稀疏表达理论的分类器，研究将二、三维图像特征融合识别人脸表情的策略。本项目首先研究了基于最大类间差别图像的二维表情特征和基于深度图像的三维表情特征的提取方法，接着将提取的特征构成字典分别结合基于稀疏表达理论的分类器得到多种识别结果，然后利用基于不同特征分类方法识别结果之间的互补性，分析基于贝叶斯理论的多分类器决策级融合规则，最后在含遮挡、噪声或光照不均的图像上验证方法的鲁棒性。本研究将为表情识别技术的研发开辟新途径，是一次融合二、三维图像特征进行表情识别的全新尝试，旨在提供一个通用性和适用性更好的表情识别方法框架。

中文关键词： 人脸表情识别；稀疏表达；RGBD图像；多分类器融合

英文摘要： Currently, one of the most difficult problems needed to be solved in the field of facial expression recognition is how to build a recognition method robust to occlusions, corruptions and various illuminations. Sparse representation based classification (SRC) method is proposed by simulating biological visual system, and previous studies have demonstrated it has a certain robustness to occlusions and corruptions. This project intends to extract the two-dimensional features and three-dimensional features from RGBD images, and uses these features combined with SRC to generate different recognition methods, and analyze the fusion strategy of different classification methods with different features. This applicant firstly studies the extraction methods of two-dimensional facial expression features based on largest-differences- between-classes images and three-dimensional expression features based on depth images, and then use SRC combined with those features to classify facial expressions and acquire numerous identify results, and analyze the fusion strategy of multiple classifiers based on Bayesian theory to fuse those results because of the complementarity between different results of recognition methods, and finally test the robustness of proposed facial expression recognition method on the images with occlusions, corruptions and various illuminations. This study will open up new ways for developing facial expression recognition technology; a new attempt to recognize facial expressions by fusing two-dimensional and three-dimensional image features, and aims to provide an expression recognition framework with better versatility and applicability.

英文关键词： Facial expression recognition;Sparse representation;RGBD Images;Fusion of multiple classifiers