Combining local features for robust nose location in 3D facial data

Due to the wide use of human face images, it is significant to locate facial feature points. In this paper, we focus on 3D facial data and propose a novel method to solve a specific problem, i.e., locating the nose tip by one hierarchical filtering scheme combining local features. Based on the detected nose tip, we further estimate the nose ridge by a newly defined curve, the Included Angle Curve (IAC). The key features of our method are its automated implementation for detection, its ability to deal with noisy and incomplete input data, its invariance to rotation and translation, and its adaptability to different resolutions. The experimental results from different databases show the robustness and feasibility of the proposed method.