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

Authors:
Chenghua Xu;Tieniu Tan;Yunhong Wang;Long Quan
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, PR China;School of Computer Science and Engineering, Beihang University, Beijing 100083, PR China;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

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.