[1]SHI Yating,LI Weijun,NING Xin,et al.A facial feature point locating algorithmbased on mouth-state constraints[J].CAAI Transactions on Intelligent Systems,2016,11(5):578-585.[doi:10.11992/tis.201602006]
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A facial feature point locating algorithmbased on mouth-state constraints

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 5 Page number: 578-585 Column: 学术论文—机器感知与模式识别 Public date: 2016-11-01
Title:
A facial feature point locating algorithmbased on mouth-state constraints
Author(s):
SHI Yating;  LI Weijun;  NING Xin;  DONG Xiaoli;  ZHANG Liping
Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
Keywords:
facial feature points location; ESR; mouth-state classifier; strong shape constraint; HSV color space; convolutional neural network
CLC:
TP183
DOI:
10.11992/tis.201602006
Abstract:
The precise locations of the feature points of the mouth critically influence applications which use feature matching, expression analysis, lip recognition and driving behavior analysis, etc. However, when estimating facial shapes using current facial landmarks detecting methods, the locating error of feature points around the mouth region is relatively large. In order to solve this problem, two kinds of‘mouth-state’classifiers were proposed, one was based on HSV color space and the other on a convolutional neural network, with a strong shape constraint strategy focusing on the spatial relationship between local facial landmarks. Furthermore a facial feature point locating method was presented based on the mouth-state constraint, which constrains the predicted explicit shape regression (ESR) result and is more accurate as regards locating facial landmarks. Compared with the original ESR algorithm, this method significantly improves the accuracy of locating landmarks for the mouth for both the Helen and LFPW datasets, and has no impact on the robustness of facial shape prediction.
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