A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of the chin and cheek contours for precise face model adaptation
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Real-Time, Fully Automatic Upper Facial Feature Tracking
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
MAP estimation of chin and cheek contours in video sequences
EURASIP Journal on Applied Signal Processing
Facial Feature Extraction and Change Analysis Using Photometric Stereo
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Automatic detailed localization of facial features
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Detecting Facial Expressions for Monitoring Patterns of Emotional Behavior
International Journal of Monitoring and Surveillance Technologies Research
Emotion recognition from geometric facial features using self-organizing map
Pattern Recognition
Hi-index | 0.01 |
This paper proposes a novel method for extraction of eyebrow contour and chin contour. We first segment rough eyebrow regions using spatial constrained sub-area K-means clustering. Then eyebrow contours are extracted by Snake method with effective image force. For chin contour extraction, we first estimate several possible chin locations which are used to build a number of curves as chin contour candidates. Based on the chin like edges extracted by proposed chin edge detector, the curve with the largest likeliness to be the actual chin contour is selected. Finally, the credible extracted eyebrow contour and the estimated chin contours are used as geometric features for face recognition. Experimental results show that the proposed algorithms can extract eyebrow contours and chin contours with good accuracy and the extracted features are effective for improving face recognition rates.