Effective semantic features for facial expressions recognition using SVM
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Summary
It is demonstrated that the proposed semantic facial features could effectively represent changes between facial expressions and the time complexity could be lower than the other SVM based approaches due to the less number of deployed features.
- Type
- article
- Published
- 2016-06-01
- Cited by
- 59
- References
- 60
- OpenAlex
- https://openalex.org/W1988518090
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:192596
Keywords
Computer science, Facial expression, Artificial intelligence, Support vector machine, Pattern recognition (psychology)
References
- Digital Image Processing
- Multiple Classifier Systems
- DEPARTMENT OF COMPUTER SCIENCE AND INFORMATION ENGINEERING
- Multiple classifier systems : 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007 : proceedings
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- Face Expression Recognition and Analysis: The State of the Art
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- Frame-Based Facial Expression Recognition Using Geometrical Features
- 3D human face description: landmarks measures and geometrical features
- Local binary patterns for multi-view facial expression recognition
- Facial expression recognition using geometric and appearance features
- Facial expression recognition and synthesis based on an appearance model
- Recognition of facial expressions using Gabor wavelets and learning vector quantization
- Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters.
- Facial Expression Recognition Using Model-Based Feature Extraction and Action Parameters Classification
- Fully Automatic Recognition of the Temporal Phases of Facial Actions
- 3D Landmarking in Multiexpression Face Analysis: A Preliminary Study on Eyebrows and Mouth
- Automatic Facial Expression Recognition Using Gabor Filter and Expression Analysis
- A principal component analysis of facial expressions.
- Active Shape Models-Their Training and Application
Cited by
- Facial expression recognition through adaptive learning of local motion descriptor
- Recognizing facial expressions using novel motion based features
- Evolving the SVM model based on a hybrid method using swarm optimization techniques in combination with a genetic algorithm for medical diagnosis
- Geometrical Approaches for Facial Expression Recognition Using Support Vector Machines
- A Multi-Layer Fusion-Based Facial Expression Recognition Approach with Optimal Weighted AUs
- A Real-Time System for Facial Expression Recognition using Support Vector Machines and k-Nearest Neighbor Classifier
- Neural network with deep learning architectures
- Face expression recognition system based on ripplet transform type II and least square SVM
- Facial expression classification using salient pattern driven integrated geometric and textual features
- Emotion recognition from geometric fuzzy membership functions
- MQSMER: a mixed quadratic shape model with optimal fuzzy membership functions for emotion recognition
- A deep learning based framework for converting sign language to emotional speech
- Stress assessment based on Ergonomics coupled with image-processing tools and techniques for lean product design and development
- GLAUCOMA DIAGONSIS FCM_TK ALGORITHM BASED ON FUNDS CAMERA
- Facial expression recognition techniques: a comprehensive survey
- A novel deep network architecture for reconstructing RGB facial images from thermal for face recognition
- On the optimal solution to maximum margin projection pursuit
- Human vision inspired feature extraction for facial expression recognition
- MDTP: a novel multi-directional triangles pattern for face expression recognition
- Recognition of Facial Expressions under Varying Conditions Using Dual-Feature Fusion
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