Exploring visual features through Gabor representations for facial expression detection
Chew, Sien Wei, Lucey, Patrick J., Sridharan, Sridha, & Fookes, Clinton B. (2010) Exploring visual features through Gabor representations for facial expression detection. In Proceedings of International Conference on Auditory-Visual Speech Processing (AVSP2010), The Prince Hakone, Hakone, Kanagawa. (In Press)
Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the
complex cells, which causes subtle differences in the responses.
In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.
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|Item Type:||Conference Paper|
|Keywords:||action unit detection, AdaBoost feature selection, Log-Gabor filter, Gabor energy filter|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2010 The Authors|
|Deposited On:||22 Jul 2010 09:26|
|Last Modified:||01 Mar 2012 00:26|
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