Toward a more robust facial expression recognition in occluded images using randomly sampled Gabor based templates


Autoria(s): Zhang, Ligang; Tjondronegoro, Dian W.; Chandran, Vinod
Data(s)

2011

Resumo

Occlusion is a big challenge for facial expression recognition (FER) in real-world situations. Previous FER efforts to address occlusion suffer from loss of appearance features and are largely limited to a few occlusion types and single testing strategy. This paper presents a robust approach for FER in occluded images and addresses these issues. A set of Gabor based templates is extracted from images in the gallery using a Monte Carlo algorithm. These templates are converted into distance features using template matching. The resulting feature vectors are robust to occlusion. Occluded eyes and mouth regions and randomly places occlusion patches are used for testing. Two testing strategies analyze the effects of these occlusions on the overall recognition performance as well as each facial expression. Experimental results on the Cohn-Kanade database confirm the high robustness of our approach and provide useful insights about the effects of occlusion on FER. Performance is also compared with previous approaches.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/40758/

Publicador

IEEE

Relação

http://eprints.qut.edu.au/40758/1/c40758.pdf

DOI:10.1109/ICME.2011.6012015

Zhang, Ligang, Tjondronegoro, Dian W., & Chandran, Vinod (2011) Toward a more robust facial expression recognition in occluded images using randomly sampled Gabor based templates. In Proceedings of 2011 IEEE International Conference on Multimedia and Expo, IEEE, a Salle - Universitat Ramon Llull, Barcelona.

Direitos

Copyright 2011 IEEE

Fonte

Faculty of Built Environment and Engineering; Faculty of Science and Technology; Information Systems; School of Engineering Systems

Palavras-Chave #080106 Image Processing #Facial expression recognition #face occlusion #Gabor #support vector machine
Tipo

Conference Paper