Tutorial: Introduction to Emotion Recognition for Digital Images

Abstract : Humans can use vision to identify objects quickly and accurately. Computer Vision seeks to emulate human vision by analyzing digital image inputs. For humans to detect an emotion will not be a difficult job to perform as humans are linked with emotions themselves but for a computer detecting an emotion will be difficult job to perform. Detecting emotion through voice, for example: detecting ‘stress' in a voice by setting parameters in areas like tone, pitch, pace, volume etc can be achieved but in case of digital images detecting emotion just by analyzing images is a novel way. The algorithm we proposed first detects facial regions in the image using a skin color model using RGB and HSV color space. Then lip region is extracted from the face region using the lip color model YCrCb color space. All the above color space uses a definite threshold value to differentiate between the regions of interest. Finally after the extraction of lip region from the image, it is compared with the series of templates and on the basis of best correlated template emotion is recognized. The proposed method is simple and fast compared to neural analysis of facial region as a whole. A simple pre defined database will be needed to help detecting various emotions that can be recognized using lip region. Size of database will affect the effectiveness of the proposed algorithm.
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Contributeur : Vinay Kumar <>
Soumis le : mercredi 2 février 2011 - 12:49:58
Dernière modification le : mardi 17 avril 2018 - 11:52:01
Document(s) archivé(s) le : mardi 3 mai 2011 - 02:26:15


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Vinay Kumar, Arpit Agarwal, Kanika Mittal. Tutorial: Introduction to Emotion Recognition for Digital Images. [Technical Report] 2011. 〈inria-00561918〉



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