基于多模态人脸与人耳融合的身份识别与认证

Human identification and verification based on multimodal fusion of face and ear

针对综合二维与三维多模态特征的正面人脸、侧面人脸与人耳的融合识别开展了相关研究，提出了二维纹理图像和三维形状索引图像的尺度空间特征提取与匹配的方法，并对多模态人脸与入耳的多种融合策略进行了探索性的研究。此方法通过使用尺度空间局部特征，消除了尺度变化的影响，对噪声、数据缺失等具有较高的鲁棒性。在公开的FRGCv2．0数据库和UNDCollectionF数据库上的实验结果表明，人脸与人耳多模态特征间的融合大幅度提高了身份识别与认证的精度，并对表情变化具有很好的鲁棒性。

This paper addresses the problem of multimodal fusion of frontal and profile face with ear for human identification and verification. A scale space local feature matching method is proposed to match both 2D texture and 3D shape index images, and various muhimodal fusion strategies are investigated. Owning to use of the advantage of scale space local fea- tures, the proposed method is insensitive to scale variations, and is robust against noise and data incompleteness. The re- sults of the experiment on the FRGC v2.0 and UND Collection F databases showed that the method＇ s outstanding identification and verification accuracy was achieved, with the high robustness against expression variations because of the fusion of multimodal features.