Multiple Regions Matching with Spin Images for 3D Face Recognition
Cheng Zhang · Journal of Information and Computational Science · 2014
This paper presents a novel method for 3D face recognition under expression and occlusion variations. It is based on the combination of the matching results from matching multiple partial regions on the 3D face. Spin image features are used for comparison between faces. Meanwhile, an efficient approach is proposed to detect nose tip and the nose tip determines the location of each candidate region. To fuse the contribution of each region, score-based and rank-based fusion scheme are performed and compared. The proposed method is evaluated on the Bosphorus database and achieves good results. It obtains 96.68% recognition rate in the presence of expression and occlusion variations.