Active shape models—their training and application
Computer Vision and Image Understanding
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
An accurate active shape model for facial feature extraction
Pattern Recognition Letters
Video Facial Feature Tracking with Enhanced ASM and Predicted Meanshift
ICCMS '10 Proceedings of the 2010 Second International Conference on Computer Modeling and Simulation - Volume 02
Automatic landmark location with a combined active shape model
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
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The active shape model (ASM) has been successfully applied to locate facial landmarks. However, in some exaggerated facial expressions, such as surprise, laugh and provoked eyebrows, it is prone to make mistaken detection. To overcome this difficulty, we propose a two-stage facial landmark detection algorithm. In the first stage, we focus on detecting the individual salient corner-type facial landmarks by applying a commonly-used Adaboosting-based algorithm, and then further apply a global ASM to refine the positions of these landmarks iteratively. In the second stage, the individual detection results of the corner-type facial landmarks serve as the initial positions of active shape model which can be further iteratively refined by an ASM algorithm. Experimental results demonstrate that the proposed method can achieve very good performance in locating facial landmarks and it consistently and considerably outperforms the traditional ASM method.