Emotion Recognition Using Feature-level Fusion of Facial Expressions and Body Gestures
Title | Emotion Recognition Using Feature-level Fusion of Facial Expressions and Body Gestures |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Keshari, Tanya, Palaniswamy, Suja |
Conference Name | 2019 International Conference on Communication and Electronics Systems (ICCES) |
Date Published | July 2019 |
Publisher | IEEE |
ISBN Number | 978-1-7281-1261-9 |
Keywords | automatic emotion recognition, bimodal emotion recognition, body gestures, collective visual conduits, Computer vision, Conferences, EEG signals, emotion recognition, Face, face recognition, facial emotion recognition, facial expressions, facial recognition, feature extraction, feature-level, Feature-level fusion, gesture recognition, hog feature, Human Behavior, human emotional behaviour, human factors, human robot interaction, image fusion, Metrics, psychological research findings, psychology, pubcrawl, real-world applications, resilience, Resiliency, sign language recognition, Support vector machines, SVM, upper body pose, virtual reality |
Abstract | Automatic emotion recognition using computer vision is significant for many real-world applications like photojournalism, virtual reality, sign language recognition, and Human Robot Interaction (HRI) etc., Psychological research findings advocate that humans depend on the collective visual conduits of face and body to comprehend human emotional behaviour. Plethora of studies have been done to analyse human emotions using facial expressions, EEG signals and speech etc., Most of the work done was based on single modality. Our objective is to efficiently integrate emotions recognized from facial expressions and upper body pose of humans using images. Our work on bimodal emotion recognition provides the benefits of the accuracy of both the modalities. |
URL | https://ieeexplore.ieee.org/document/9002175 |
DOI | 10.1109/ICCES45898.2019.9002175 |
Citation Key | keshari_emotion_2019 |
- pubcrawl
- Human behavior
- human emotional behaviour
- Human Factors
- Human Robot Interaction
- image fusion
- Metrics
- psychological research findings
- psychology
- hog feature
- real-world applications
- resilience
- Resiliency
- sign language recognition
- Support vector machines
- SVM
- upper body pose
- virtual reality
- face recognition
- bimodal emotion recognition
- body gestures
- collective visual conduits
- computer vision
- Conferences
- EEG signals
- emotion recognition
- Face
- automatic emotion recognition
- facial emotion recognition
- facial expressions
- facial recognition
- feature extraction
- feature-level
- Feature-level fusion
- gesture recognition