Recognizing action units for facial expression analysis
نویسندگان
چکیده
منابع مشابه
Recognizing Action Units for Facial Expression Analysis
Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more often communicated by changes in one or a few discrete facial features. In this paper, we develop an Automatic Face Analysis (AFA) system to ana...
متن کاملRecognizing Lower Face Action Units for Facial Expression Analysis
Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions (e.g. happiness and anger). Such prototypic expressions, however, occur infrequently. Human emotions and intentions are communicated more often by changes in one or two discrete facial features. In this paper, we develop an automatic system to analyze subtle changes in facial expressions based ...
متن کاملRecognizing Upper Face Action Units for Facial Expression Analysis
We develop an automatic system to analyze subtle changes in upper face expressions based on both permanent facial features (brows, eyes, mouth) and transient facial features (deepening of facial furrows) in a nearly frontal image sequence. Our system recognizes fine-grained changes in facial expression based on Facial Action Coding System (FACS) action units (AUs). Multi-state facial component ...
متن کاملUnifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis
Previous approaches to model and analyze facial expression analysis use three different techniques: facial action units, geometric features and graph based modelling. However, previous approaches have treated these technique separately. There is an interrelationship between these techniques. The facial expression analysis is significantly improved by utilizing these mappings between major geome...
متن کاملRecognizing facial action units using independent component analysis and support vector machine
Facial expression provides a crucial behavioral measure for studies of human emotion, cognitive processes, and social interaction. In this paper, we focus on recognizing facial action units (AUs), which represent the subtle change of facial expressions. We adopt ICA (independent component analysis) as the feature extraction and representation method and SVM (support vector machine) as the patte...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2001
ISSN: 0162-8828
DOI: 10.1109/34.908962