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http://dx.doi.org/10.7746/jkros.2013.8.2.104

Facial Feature Tracking Using Adaptive Particle Filter and Active Appearance Model  

Cho, Durkhyun (Department of Electronics and Computer Engineering, Hanyang University)
Lee, Sanghoon (Department of Intelligent Robot Engineering, Hanyang University)
Suh, Il Hong (Department of Computer Sciences and Engineering, College of Engineering, Hanyang University)
Publication Information
The Journal of Korea Robotics Society / v.8, no.2, 2013 , pp. 104-115 More about this Journal
Abstract
For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.
Keywords
facial feature tracking; particle filter; active appearance model; human-robot interaction;
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