Three-dimensional face recognition using nose region features and an efficient variant of the iterative closest point algorithm - Trần Tiến Đức (Journal of Technical Education Science, 2017)
Facial recognition has attracted much research interest recently for its applicability in various domains such as security and marketing. Three-dimensional face recognition approaches have been proved more robust than two-dimensional ones in dealing with changes in illumination condition, head orientations, facial expressions and make up. In this paper, we apply an efficient variant of the iterative closest point algorithm to align two three-dimensional point sets using nose region features for three-dimensional face recognition. The author demonstrates the proposed method with numerical experiment on Gavab3D data set including 427 facial images of 61 people. The experimental result shows that the proposed method performs well with accuracy of 92%.