Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55500
Title: Kinect Joints Correction Using Optical Flow for Weightlifting Videos
Authors: Pichamon Srisen
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Samatchai Chamnongkich
Keywords: Computer Science
Mathematics
Issue Date: 29-Sep-2016
Abstract: © 2015 IEEE. To ease a coach in weightlifting training, automatic weightlifting pattern evaluation is required. In order to do that, the motion tracking process is always needed. Kinect sensor is one of the popular sensors for that. However, there is a problem with skeleton created by the Kinect sensor because of self-occlusion. Hence, in this paper, we develop a joint correction process for 3 types of joints including hands, feet, and knees since these joints are sometimes provided incorrectly. However, we only correct these joints in the "the first pull to the transition from the first to the second pull" (first-step) in snatch, and clean and jerk weightlifting and "the turnover under the barbell to the catch phase" (second-step) in clean and jerk weightlifting. This is because miscalculation occurs only in these steps. We utilized fast cross-correlation and the Lucas-Kanade algorithm to compute the optical flow of the consecutive frames. From that, we then correct the joints if they are misplaced from the predicted joints. Our system provides better joints and more preferable to human eyes than the original Kinect skeleton.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84994323457&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55500
ISSN: 21668531
21668523
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.