Technical Papers Session IV: A new perspective towards analysis of human facial expression using supervised classification algorithms
Abstract/Description
As cost-effective and relatively accurate models for behavior classification, automatic facial expression analysis has the potential to be applied to multiple disciplines. The current research deals with real-time classification of evoked emotions in children. Reason behind analyzing children behavior is that they possess immature cognitive abilities compared to adults, they are more likely to be influenced by external stimuli and they are less likely to pose and hide expression. This research work uses a three-phase classification model to analyze real time captured emotion varying children facial expressions. Two classifiers K-Nearest Neighbor and SVM were used for classification. The classification model was tested using our own real time recorded children Facial Expression (CFE).
Keywords
Face detection, Feature extraction, Eigenface, KNN, SVM, Voila Jones, Facial expression
Location
Lecture Hall A (Aman Tower, 12th floor)
Session Theme
Technical Papers Session IV - Artificial Intelligence
Session Type
Parallel Technical Session
Session Chair
Engr. Parkash Lohana
Start Date
17-11-2019 2:20 PM
End Date
17-11-2019 2:40 PM
Recommended Citation
Iqbal, T., & Javed, S. T. (2019). Technical Papers Session IV: A new perspective towards analysis of human facial expression using supervised classification algorithms. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/33
COinS
Technical Papers Session IV: A new perspective towards analysis of human facial expression using supervised classification algorithms
Lecture Hall A (Aman Tower, 12th floor)
As cost-effective and relatively accurate models for behavior classification, automatic facial expression analysis has the potential to be applied to multiple disciplines. The current research deals with real-time classification of evoked emotions in children. Reason behind analyzing children behavior is that they possess immature cognitive abilities compared to adults, they are more likely to be influenced by external stimuli and they are less likely to pose and hide expression. This research work uses a three-phase classification model to analyze real time captured emotion varying children facial expressions. Two classifiers K-Nearest Neighbor and SVM were used for classification. The classification model was tested using our own real time recorded children Facial Expression (CFE).
