Implementation and evaluation of "just follow me": an immersive, VR-based, motion-training system
Presence: Teleoperators and Virtual Environments
Training for Physical Tasks in Virtual Environments: Tai Chi
VR '03 Proceedings of the IEEE Virtual Reality 2003
Multimodal presentation method for a dance training system
CHI '05 Extended Abstracts on Human Factors in Computing Systems
A Control System for a Flexible Spine Belly-Dancing Humanoid
Artificial Life
Using real-time acceleration data for exercise movement training with a decision tree approach
Expert Systems with Applications: An International Journal
Real-time mocap dance recognition for an interactive dancing game
Computer Animation and Virtual Worlds
A Virtual Reality Dance Training System Using Motion Capture Technology
IEEE Transactions on Learning Technologies
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Autonomous robot dancing driven by beats and emotions of music
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
| Hi-index | 0.00 |
Collapsed formation in a group dance will greatly reduce the quality of the performance even if the dance in the group is synchronized with music. Therefore, learning the formation of a dance in a group is as important as learning its choreography. However, if someone cannot participate in practice, it is difficult for the rest of the members to gain a sense of the proper formation in practice. We propose a practice-support system for performing the formation smoothly using a self-propelled screen even if there is no dance partner. We developed a prototype of the system and investigated whether a sense of presence provided by both methods of practicing formations was close to the sense we really obtain when we dance with humans. The result verified that the sense of dancing with a projected video was closest to the sense of dancing with a dancer, and the trajectory information from dancing with a self-propelled robot was close to the trajectory information from dancing with a dancer. Practicing in situations similar to real ones is able to be done by combining these two methods. Furthermore, we investigated whether the self-propelled screen obtained the advantages of dancing with both methods and found that it only obtained advantages of dancing with projected video.