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http://dx.doi.org/10.3837/tiis.2015.09.022

Robust Three-step facial landmark localization under the complicated condition via ASM and POEM  

Li, Weisheng (Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications)
Peng, Lai (Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications)
Zhou, Lifang (Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.9, no.9, 2015 , pp. 3685-3700 More about this Journal
Abstract
To avoid influences caused by pose, illumination and facial expression variations, we propose a robust three-step algorithm based on ASM and POEM for facial landmark localization. Firstly, Model Selection Factor is utilized to achieve a pose-free initialized shape. Then, we use the global shape model of ASM to describe the whole face and the texture model POEM to adjust the position of each landmark. Thirdly, a second localization is presented to discriminatively refine the subtle shape variation for some organs and contours. Experiments are conducted in four main face datasets, and the results demonstrate that the proposed method accurately localizes facial landmarks and outperforms other state-of-the-art methods.
Keywords
Facial Landmark Localization; Active Shape Model (ASM); Model Selection Factor (MSF); Patterns of Oriented Edge Magnitudes (POEM); Pattern Recognition;
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