Yoga posture recognition for self-training

Hua Tsung Chen, Yu Zhen He, Chun Chieh Hsu, Chien Li Chou, Suh Yin Lee, Bao-Shuh Lin 

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

16 Scopus citations


Self-training plays an important role in sports exercise, but improper training postures can cause serious harm to muscles and ligaments of the body. Hence, more and more researchers are devoted into the development of computer-assisted self-training systems for sports exercise. In this paper, we propose a Yoga posture recognition system, which is capable of recognizing what Yoga posture the practitioner is performing, and then retrieving Yoga training information from Internet to remind his/her attention to the posture. First, a Kinect is used for capturing the user body map and extracting the body contour. Then, star skeleton, which is a fast skeletonization technique by connecting from centroid of target object to contour extremes, is used as a representative descriptor of human posture for Yoga posture recognition. Finally, some Yoga training information for the recognized posture can be retrieved from Internet to remind the practitioner what to pay attention to when practicing the posture.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings
Number of pages10
EditionPART 1
StatePublished - 7 Feb 2014
Event20th Anniversary International Conference on MultiMedia Modeling, MMM 2014 - Dublin, Ireland
Duration: 6 Jan 201410 Jan 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8325 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference20th Anniversary International Conference on MultiMedia Modeling, MMM 2014


  • feature extraction
  • Kinect
  • posture analysis
  • sports training
  • star skeleton
  • Yoga


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