Paper Info
Title
Emotion recognition using facial and audio features
Abstract
Human Computer Interaction is an upcoming scientific field which aims at inter-communication between humans and computers. A major element of this field is Human Emotion Recognition. The most expressive way humans display emotions is through facial expressions. Traditionally, emotion recognition has been performed on laboratory controlled data. While undoubtedly worthwhile at the time, such lab controlled data poorly represents the environment and conditions faced in real-world situations. With the increase in the number of video clips online, it is worthwhile to explore the performance of emotion recognition methods that work 'in the wild' .This work mainly focuses on automatic emotion recognition in a wild video sample. In this task, we have worked on the problem of human emotion recognition using a combination of video features and audio features. The technique that we have utilized for emotion detection involves a blend of Optical flow, Gabor Filtering, few other facial features and audio features. Training and Classification is performed using Support Vector Machine-Hidden Markov Model (HMM). The unique thing about our methodology is that it produces better results for some particular class of emotions as compared to the baseline score in the case of wild emotion dataset with an overall accuracy of 20.51% on the test set.
Year
DOI
Venue
2013
10.1145/2522848.2531746
ICMI
Keywords
DocType
Citations 
automatic emotion recognition,video feature,emotion recognition,human emotion recognition,video clips online,emotion recognition method,wild emotion dataset,audio feature,wild video sample,emotion detection,support vector machine,optical flow,hidden markov model
Conference
2
PageRank 
References 
Authors
0.37
11
6
Name
Order
Citations
PageRank
Tarun Krishna1311.34
Ayush Rai2311.34
Shubham Bansal3341.80
Shubham Khandelwal4352.17
Shubham Gupta527827.57
Dushyant Goyal6415.21