非受控场景下融合结构与纹理信息的人脸人耳多模态识别

项目名称： 非受控场景下融合结构与纹理信息的人脸人耳多模态识别

项目编号： No.61472031

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 其他

项目作者： 穆志纯

作者单位： 北京科技大学

项目金额： 80万元

中文摘要： 为实现更为鲁棒的非受控场景下的身份识别,克服单一模态识别的不足，本项目将通过球面变换方法将采集到的人脸人耳数据转换为以识别对象为中心进行表达，进而生成MARS图，即多模态人脸人耳球面深度图与球面纹理图。MARS图自然融合了人脸人耳两种模态，包含了更完整的结构信息和纹理信息，有助于克服人脸、人耳单模态识别中姿态、表情、年龄、遮挡问题带来的影响；消除了平面外旋转，有助于后续实现无需对准、对姿态鲁棒的识别；其二维表达形式可减少数据存储开销，降低识别过程的计算复杂度。非受控下的身份识别从根本上是利用部分数据所进行的识别，因此本项目研究基于MARS图局部特征的融合识别方法，内容涉及：人脸人耳二维三维数据表达转换，高鉴别性的快速鲁棒局部特征描述子构造，基于人脸人耳部分数据的结构信息与纹理信息融合识别策略等，其结果不仅对基于人脸人耳的非受控身份识别，而且对更广泛领域中的应用基础和理论研究都将是有意义的。

中文关键词： 非受控身份识别；人脸人耳多模态识别；球面深度图和球面纹理图；部分数据；局部特征

英文摘要： To achieve more robust personal identification in unconstrained environments and overcome the shortcomings exhibited in uni-modal recognition that uses face or ear, this project proposes a scheme that starts with converting the acquired face and ear data by spherical transform to the form that is the object-centered. Mapping the converted data onto sphere surface, Multimodal fAce and eaR Spherical depth map and texture map (MARS maps) are then obtained. With MARS depth map and MARS texture map, two modals, face and ear, are naturally fused together and more complete structural and textural information are made available, which is definitely helpful to alleviate the problems induced by pose variations, facial expression, aging and occlusion when using face or ear alone for recognition. These spherical maps, in addition, are invariant to out-plane rotation, subsequently facilitating the successive alignment-free identification that is robust to pose variations. Meanwhile, the way of data presenting of the maps in 2D form reduces the overhead of data storage and the load of computation involved in recognition process. Personal identification in unconstrained environments is basically the identification that uses partial data. Therefore, this project will try to explore face and ear recognition methods based on the local features extracted from MARS maps. The scope of research of this project covers convertion method of structural and textural data of face and ear; construction of fast, highly discriminative and robust local feature descriptors; partial face and ear recognition strategy fusing structural information and textural information, etc. The output of the project is expected to contribute not only to the face and ear based multimodal personal identification in unconstrained environments, but also to theoretical and practical research in the areas that are relevant.

英文关键词： personal identification in unconstrained environments;face and ear based multimodal biometrics;spherical depth map and spherical texture map;partial data;local feature