Abstract
We present a real-time algorithm for human pose detection and tracking from vision-based 3D data and its application to tele-rehabilitation in virtual environments. We employ stereo camera(s) to capture 3D avatars of geographically dislocated patient and therapist in real-time, while sending the data remotely and displaying it in a virtual scene. A pose detection and tracking algorithm extracts kinematic parameters from each participant and determines pose similarity. The pose similarity score is used to quantify patient's performance and provide real-time feedback for remote rehabilitation.
| Original language | English (US) |
|---|---|
| Title of host publication | Studies in Health Technology and Informatics |
| Pages | 320-324 |
| Number of pages | 5 |
| Volume | 173 |
| DOIs | |
| State | Published - 2012 |
| Event | Medicine Meets Virtual Reality 19: NextMed, MMVR 2012 - Newport Beach, CA, United States Duration: Feb 9 2012 → Feb 11 2012 |
Other
| Other | Medicine Meets Virtual Reality 19: NextMed, MMVR 2012 |
|---|---|
| Country | United States |
| City | Newport Beach, CA |
| Period | 2/9/12 → 2/11/12 |
Keywords
- Human pose estimation and tracking
- Stereo vision
- Tele-rehabilitation
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
- Health Information Management
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Obdržálek, Š., Kurillo, G., Han, J., Abresch, T., & Bajcsy, R. (2012). Real-time human pose detection and tracking for tele-rehabilitation in virtual reality. In Studies in Health Technology and Informatics (Vol. 173, pp. 320-324) https://doi.org/10.3233/978-1-61499-022-2-320