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T-Space at The University of Toronto Libraries >
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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/30639

Title: Emotion Recognition from Eye Region Signals using Local Binary Patterns
Authors: Jain, Gaurav
Advisor: Plataniotis, Konstantinos N.
Department: Electrical and Computer Engineering
Keywords: Emotion Recognition
Eye Region
Local Binary Patterns
Implicit Tagging of Multimedia Content
Facial Expression Recognition
Issue Date: 8-Dec-2011
Abstract: Automated facial expression analysis for Emotion Recognition (ER) is an active research area towards creating socially intelligent systems. The eye region, often considered integral for ER by psychologists and neuroscientists, has received very little attention in engineering and computer sciences. Using eye region as an input signal presents several bene ts for low-cost, non-intrusive ER applications. This work proposes two frameworks towards ER from eye region images. The first framework uses Local Binary Patterns (LBP) as the feature extractor on grayscale eye region images. The results validate the eye region as a signi cant contributor towards communicating the emotion in the face by achieving high person-dependent accuracy. The system is also able to generalize well across di erent environment conditions. In the second proposed framework, a color-based approach to ER from the eye region is explored using Local Color Vector Binary Patterns (LCVBP). LCVBP extend the traditional LBP by incorporating color information extracting a rich and a highly discriminative feature set, thereby providing promising results.
URI: http://hdl.handle.net/1807/30639
Appears in Collections:Master

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