Robust nose detection and tracking using gentleboost and improved Lucas-Kanade optical flow algorithms

Authors:
Xiaobo Ren;Jiatao Song;Hongwei Ying;Yani Zhu;Xuena Qiu
Affiliations:
College of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, P.R. China;College of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, P.R. China;College of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, P.R. China;College of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, P.R. China;College of Electronic and Information Engineering, Ningbo University of Technology, Ningbo, P.R. China
Venue:
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Year:
2007

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Abstract

The problem of face feature points detection is an important research topic in many fields such as face image analysis and human-machine interface. In this paper, we propose a robust method of 2D nose detection and tracking system. This system can be valuable for disabled people or for cases where hands are busy with other tasks. The required information is derived from video data captured with an inexpensive web camera. Position of the nose tip is determined with the use of a Gabor wavelet feature based GentleBoost detector. Once the nose tip is initially located, an improved Lucas-Kanade optical flow method is used to track the nose tip feature point. Experiments show that our system is able to process 18 frames per second at a resolution of 320×240 pixels. This method will in future be used in a non-contact interface for disabled users.