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
Robust Active Shape Model Search
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
View-Based Active Appearance Models
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Shape Localization Based on Statistical Method Using Extended Local Binary Pattern
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Active Shape Models with Invariant Optimal Features: Application to Facial Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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In this paper, we proposed an improved coarse to fine improved algorithm to enhance the accuracy of facial key landmark points locating. Based on the analysis of PCA, the proposed algorithm redesigns the parameter update rule through adding a monotonically decreasing inert factor function to the traditional ASM iterations (D-ASM). The new rule could update parameters at a finer process. Besides, we compare the performances of different types of inert factor functions and select the suitable one. Furthermore, we further design a classifier-based algorithm for the more accurate locating of 2D key corner points. Finally, local D-ASM is constructed and the inner landmarks are further fitting with corner points fixed. Experimental results on various faces demonstrate the effectiveness and rationality of our proposed algorithm.