@inproceedings{f0f6c59a57be4929a02a7a16e3fcf84c,
title = "Yoga posture recognition for self-training",
abstract = "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.",
keywords = "feature extraction, Kinect, posture analysis, sports training, star skeleton, Yoga",
author = "Chen, {Hua Tsung} and He, {Yu Zhen} and Hsu, {Chun Chieh} and Chou, {Chien Li} and Lee, {Suh Yin} and Bao-Shuh Lin ",
year = "2014",
month = feb,
day = "7",
doi = "10.1007/978-3-319-04114-8_42",
language = "English",
isbn = "9783319041131",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "496--505",
booktitle = "MultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings",
edition = "PART 1",
note = "20th Anniversary International Conference on MultiMedia Modeling, MMM 2014 ; Conference date: 06-01-2014 Through 10-01-2014",
}