Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Action Units for Facial Expression Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Connected Vibrations: A Modal Analysis Approach for Non-Rigid Motion Tracking
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Online Facial Expression Recognition Based on Personalized Galleries
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
PersonSpotter - Fast and Robust System for Human Detection, Tracking and Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Model-Based Face Tracking for View-Independent Facial Expression Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Real time facial expression recognition in video using support vector machines
Proceedings of the 5th international conference on Multimodal interfaces
Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 10 - Volume 10
Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial Expression Recognition Based on Selective Feature Extraction
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of sexual dimorphism in human face
Journal of Visual Communication and Image Representation
Facial Complex Expression Recognition Based on Fuzzy Kernel Clustering and Support Vector Machines
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 01
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Task oriented facial behavior recognition with selective sensing
Computer Vision and Image Understanding
HCI'07 Proceedings of the 2007 IEEE international conference on Human-computer interaction
Recognition of facial expressions and measurement of levels of interest from video
IEEE Transactions on Multimedia
A real-time automated system for the recognition of human facial expressions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Hi-index | 0.00 |
Facial expression is a powerful mechanism used by humans to communicate their emotions, intentions, and opinions to each other. The recognition of facial expressions is extremely important for a responsive and socially interactive human-computer interface. Such an interface with a robust capability to recognize human facial expressions should enable an automated system to effectively deploy in a variety of applications, including human computer interaction, security, law enforcement, psychiatry, and education. In this paper, we examine several core problems in face expression analysis from the perspective of landmarks and distances between them using a statistical approach. We have used statistical analysis to determine the landmarks and features that are best suited to recognize the expressions in a face. We have used a standard database to examine the effectiveness of landmark based approach to classify an expression (a) when a face with a neutral expression is available, and (b) when there is no a priori information about the face.