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Visual affect recognition /
It is generally known that human faces, as well as body motions and gestures, provide a wealth of information about a person, such as age, race, sex and emotional state. This monograph primarily studies the perception of facial expression of emotion, and secondarily of motion and gestures, with the...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Washington, DC :
IOS Press,
2010.
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| Colección: | Frontiers in artificial intelligence and applications ;
214. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Title page; Contents; Introduction; Motivation; Organization of this monograph; Psychological Studies on Emotion Perception; Emotion vs affect vs feelings; Emotions and culture; Basic Emotions; Culturally Specific Expressions of Emotions; Higher Cognitive Emotions; Neurobiology and Emotion Expression; Cerebral Cortex; Amygdala; Superior Temporal Sulcus; Implicit and Explicit Perception of Emotion; Expression of Emotion; Written Language; Speech; Facial Expressions; Body movements and Hand gestures; Facial Expression of Emotion.
- Previous Attempts to Facial Emotion Quantification and ClassificationExternal Factors in Facial Emotion Perception; Face and Facial Expressions: Their Role; The Importance of Understanding Emotions; Meeting Emotional Needs with the Help of Advanced Human-Computer Interaction Techniques; Supporting emotional skill needs; Supporting experiential needs; Studies and Systems on Emotion Recognition; Face Databases; Specifying Requirements for an Ideal Facial Expression Database; Previous Facial Expression Databases; Section Summary
- Results; Face Detection.
- Specifying Requirements for an Ideal Face Detection SystemPrevious Works on Face Detection; Section Summary
- Results; Facial Expression Classification System; Specifying Requirements for our Facial Expression Classification System; Facial Expression Classification Approaches; Section Summary
- Results; Face Image Databases; The Database of Low Quality Face Images (DBLQFI); The Database of High Quality Face Images (DBHQFI); Empirical Studies on Emotion Recognition; Preliminary Questionnaires; Newer (Detailed) Questionnaires; The detailed questionnaire structure.
- The observer and subject backgroundsResults from Statistical Analysis; Statistical Analysis per Expression; Difficulties of Facial Expression Classification as Outlined by the Participants; Statistical Significance of the Results; Extraction of Facial Expression Classification Features; Summary
- Conclusions; Visual-Facial Emotion Recognition System; Face Detection; P. Sinha's Template; The Face Detection Algorithm
- Image Preprocessing; Artificial Neural Network-Based Face Detectors; Performance Evaluation; Summary and Conclusions; Introduction to our Facial Expression Recognition System.
- First attempts for facial expression recognitionThe Facial Expression Classification Algorithm (1st Attempts); Feature Validation (First Attempts); Neural Network Classifiers (First Attempts); Results from neural network classifiers (First Attempts); Facial expression recognition system; Feature Selection; Image Preprocessing and Feature Extraction; The extraction algorithm for the rest of facial features; Combination of all and computation of feature vector; Quantification of Feature Discrimination Power; Classifiers for Facial Expression Classification; Classification Performance Assessment.