3D face recognition under partial occlusions using radial strings

3D face recognition with partial occlusions is a highly challenging problem. In this paper, we propose a novel radial string representation and matching approach to recognize 3D facial scans in the presence of partial occlusions. Here we encode 3D facial surfaces into an indexed collection of radial strings emanating from the nosetips and Dynamic Programming (DP) is then used to measure the similarity between two radial strings. In order to address the recognition problems with partial occlusions, a partial matching mechanism is established in our approach that effectively eliminates those occluded parts and finds the most discriminative parts during the matching process. Experimental results on the Bosphorus database demonstrate that the proposed approach yields superior performance on partially occluded data.