ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Facial boundary detection with an active contour model
Pattern Recognition Letters
Static topographic modeling for facial expression recognition and analysis
Computer Vision and Image Understanding
International Journal of Approximate Reasoning
Classification of face images using local iterated function systems
Machine Vision and Applications
Facial expression recognition based on shape and texture
Pattern Recognition
Emotion recognition from facial expressions and its control using fuzzy logic
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Overview of automatic facial expressions analysis
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Image ratio features for facial expression recognition application
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Studies on hyperspectral face recognition in visible spectrum with feature band selection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Image and Vision Computing
Robust frontal view search using extended manifold learning
Journal of Visual Communication and Image Representation
| Hi-index | 0.00 |
The automatic recognition of facial expression presents a significant challenge to the pattern analysis and man-machine interaction research community. Recognition from a single static image is particularly a difficult task. In this paper, we present a methodology for facial expression recognition from a single static image using line-based caricatures. The recognition process is completely automatic. It also addresses the computational expensive problem and is thus suitable for real-time applications. The proposed approach uses structural and geometrical features of a user sketched expression model to match the line edge map (LEM) descriptor of an input face image. A disparity measure that is robust to expression variations is defined. The effectiveness of the proposed technique has been evaluated and promising results are obtained. This work has proven the proposed idea that facial expressions can be characterized and recognized by caricatures.