Please use this identifier to cite or link to this item: https://doi.org/10.1109/FG.2011.5771371
Title: Accumulated motion images for facial expression recognition in videos
Authors: Srivastava, R.
Roy, S.
Yan, S. 
Sim, T. 
Issue Date: 2011
Source: Srivastava, R.,Roy, S.,Yan, S.,Sim, T. (2011). Accumulated motion images for facial expression recognition in videos. 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 : 903-908. ScholarBank@NUS Repository. https://doi.org/10.1109/FG.2011.5771371
Abstract: This paper details the method and experiments conducted towards our submission to the FERA 2011 facial expression recognition benchmarking evaluations. The benchmarking evaluation task involves recognizing 5 emotion classes in videos. Our method for detecting facial expressions is a fusion of the decisions of two FER approaches based on two different feature representations, namely using motion information from facial regions and facial feature point displacement information. The main observation motivating the approach we took is that different feature representations are discriminative in detecting different facial expressions. Hence a fusion approach could complement each other to improve recognition performance. Experiments were conducted on the GEMEP-FERA data set provided by the organizers. © 2011 IEEE.
Source Title: 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
URI: http://scholarbank.nus.edu.sg/handle/10635/43279
ISBN: 9781424491407
DOI: 10.1109/FG.2011.5771371
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