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http://dx.doi.org/10.3745/KTSDE.2013.2.3.209

Effective Pose-based Approach with Pose Estimation for Emotional Action Recognition  

Kim, Jin Ok (대구한의대학교 국제문화정보대학 모바일콘텐츠학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.2, no.3, 2013 , pp. 209-218 More about this Journal
Abstract
Early researches in human action recognition have focused on tracking and classifying articulated body motions. Such methods required accurate segmentation of body parts, which is a sticky task, particularly under realistic imaging conditions. Recent trends of work have become popular towards the use of more and low-level appearance features such as spatio-temporal interest points. Given the great progress in pose estimation over the past few years, redefined views about pose-based approach are needed. This paper addresses the issues of whether it is sufficient to train a classifier only on low-level appearance features in appearance approach and proposes effective pose-based approach with pose estimation for emotional action recognition. In order for these questions to be solved, we compare the performance of pose-based, appearance-based and its combination-based features respectively with respect to scenario of various emotional action recognition. The experiment results show that pose-based features outperform low-level appearance-based approach of features, even when heavily spoiled by noise, suggesting that pose-based approach with pose estimation is beneficial for the emotional action recognition.
Keywords
Pose-based Action Features; Appearance-based Action Features; Action Recognition; Emotional Expression Recognition; Pose Estimation;
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