Nose tip localization on a three dimensional face across pose, expressions and occlusions variations in a Riemannian context

Nose tip localization is an important step for registration, preprocessing and recognition of 3D face data. In this paper, we propose a new approach for the nose tip detection that is robust to pose and expression variations and in presence of occlusions. From a rotated 3D face, we extract facial curves that are matched to a profile curve model. An optimal matching using the Riemannian geometry, based on the Elastic Shape Analysis is performed to obtain the accurate nose tip. The proposed method requires no training and can locate the nose tip in less than 6 seconds. Experiments are performed on the Bosphorus database. Quantitative analysis and comparison with the ground truth locations are provided. The results confirm that our approach achieves 97.68% with error no larger than 12 mm and 98.19% within 20 mm.