Research on Face Recognition Based on Vertex Energy Minimum Patterns

Aiming at the loss of the geometric information of the three-dimensional surface caused by the existing three-dimensional face recognition algorithm in the process of dimension reduction, by studying the conformal geometry related knowledge, this chapter adopts the conformal mapping method based on Ricci curvature flow to reduce the three-dimensional face surfaces to two-dimensional planar disk. The geometric information in the 3D surface is not lost as much as possible thus improving the recognition efficiency in the subsequent recognition process. In this chapter, a three-dimensional face recognition method based on minimum vertex energy pattern is proposed. Each point on the surface will be given its unique energy value in the calculation process of conformal mapping through Ricci curvature flow. By counting the variation of the energy value of each vertex, the feature histogram is generated, which is used as the basis of recognition. The method achieves better recognition effect. The recognition rate has been increased to more than 95%.

[1]  David Declercq,et al.  3D face recognition using covariance based descriptors , 2016, Pattern Recognit. Lett..

[2]  Faisal R. Al-Osaimi,et al.  An Expression Deformation Approach to Non-rigid 3D Face Recognition , 2009, International Journal of Computer Vision.

[3]  Mohammed Bennamoun,et al.  A Curvelet-based approach for textured 3D face recognition , 2015, Pattern Recognit..

[4]  Frank B. ter Haar,et al.  A 3D face matching framework for facial curves , 2009, Graph. Model..

[5]  Alberto Del Bimbo,et al.  Geodesic Distances for 3D-3D and 2D-3D Face Recognition , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[6]  Pascal Frossard,et al.  3D Face Recognition with Sparse Spherical Representations , 2008, Pattern Recognit..

[7]  Di Huang,et al.  3-D Face Recognition Using eLBP-Based Facial Description and Local Feature Hybrid Matching , 2012, IEEE Transactions on Information Forensics and Security.

[8]  Qiuqi Ruan,et al.  Robust sparse bounding sphere for 3D face recognition , 2012, Image Vis. Comput..