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
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Neural Networks - Special issue: Emotion and brain
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Editorial: Hybrid learning machines
Neurocomputing
Editorial: Hybrid intelligent algorithms and applications
Information Sciences: an International Journal
A discriminative feature space for detecting and recognizing faces
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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The study presents results of analysis of spontaneous facial expression. Their purpose was to isolate aggression from the facial expressions. Based on tracking specific points of a face, selected from a video sequence, a trajectory of the face's movement was made. Then, using the Gabor filter and Local Binary Patterns (LBP) operator, extraction and analysis of the facial features was performed, from which vectors of aggression features have been detailed. Using the support vector machine (SVM) classifier, classification of the spontaneous facial data was made in order to detect the aggression. A correct recognition rate of the method, as high as 85% as well as a high ability for generalization was obtained.