Action tutor: Real-time exemplar-based sequential movement assessment with kinect sensor

Chi Wen Chen*, Min Chun Hu, Wen-Huang Cheng, Che Han Chang, Jui Hsin Lai, Ja Ling Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

With the aid of depth camera, such as Microsoft Kinect, the difficulty of vision-based posture estimation is greatly decreased, and human action analysis has achieved a wide range of applications. However, there is still much to do to develop effective movement assessment technique, which bridges the results of human posture estimation and the understanding of human action performance. In this work, we propose an action tutor system which enables the user to interactively retrieve the learning exemplar of the target action movement and to immediately acquire motion instructions while learning it in front of the Kinect. In the retrieval stage, non-linear time warping algorithms are designed to retrieve video segments similar to the query movement roughly performed by the user. In the learning stage, the user learns according to the selected video exemplar, and the motion assessment including both static and dynamic differences is presented to the user in a more effective and organized way, helping him/her to perform the action movement correctly.

Original languageEnglish
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
Pages1263-1264
Number of pages2
DOIs
StatePublished - 26 Dec 2012
Event20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
Duration: 29 Oct 20122 Nov 2012

Publication series

NameMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia

Conference

Conference20th ACM International Conference on Multimedia, MM 2012
CountryJapan
CityNara
Period29/10/122/11/12

Keywords

  • human action video retrieval
  • movement assessment

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