Name
Abstract | ||
|---|---|---|
The difficulty of vision-based posture estimation is greatly decreased with the aid of commercial depth camera, such as Microsoft Kinect. However, there is still much to do to bridge the results of human posture estimation and the understanding of human movements. Human movement assessment is an important technique for exercise learning in the field of healthcare. In this paper, we propose an action tutor system which enables the user to interactively retrieve a learning exemplar of the target action movement and to immediately acquire motion instructions while learning it in front of the Kinect. The proposed system is composed of two stages. In the retrieval stage, nonlinear 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. The experiments are conducted on the videos of ten action types, and the results show that the proposed human action descriptor is representative for action video retrieval and the tutor system can effectively help the user while learning action movements. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TCYB.2014.2335540 | IEEE T. Cybernetics |
Keywords | Field | DocType |
video signal processing,action types,learning stage,human action descriptor,real-time human movement retrieval,tutor system,human computer interaction,dynamic differences,target action movement,retrieval stage,image segmentation,nonlinear time warping,human skeleton,kinect sensor,static differences,exercise learning,real-time human movement assessment,motion estimation,motion instructions,image sensors,feature extraction,video exemplar,vision-based human posture estimation,action video retrieval,cameras,computer vision,action tutor system,learning action movements,query movement,motion assessment,nonlinear time warping algorithms,healthcare,human action,interactive video,learning exemplar,video segment retrieval,video retrieval,torso,databases,estimation,real time systems | Computer vision,TUTOR,Movement assessment,Motor activity,Dynamic time warping,Video retrieval,Computer science,Artificial intelligence,Target–action | Journal |
Volume | Issue | ISSN |
45 | 4 | 2168-2275 |
Citations | PageRank | References |
24 | 0.94 | 18 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min-Chun Hu | 1 | 170 | 29.78 |
| Chi-Wen Chen | 2 | 25 | 1.38 |
| Wen-huang Cheng | 3 | 715 | 73.78 |
| Che-Han Chang | 4 | 142 | 8.27 |
| Jui-Hsin Lai | 5 | 60 | 8.98 |
| Ja-ling Wu | 6 | 1569 | 168.11 |