Performance of optical flow techniques
International Journal of Computer Vision
Hypercomplex correlation techniques for vector images
IEEE Transactions on Signal Processing
Hands-up: motion recognition using kinect and a ceiling to improve the convenience of human life
CHI '12 Extended Abstracts on Human Factors in Computing Systems
3D-live: live interactions through 3D visual environments
Proceedings of the 2012 Virtual Reality International Conference
Evaluating user's energy consumption using kinect based skeleton tracking
Proceedings of the 20th ACM international conference on Multimedia
A tai chi training system based on fast skeleton matching algorithm
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Exploring body language as narrative interface
ICIDS'12 Proceedings of the 5th international conference on Interactive Storytelling
Interactive virtual try-on based on real-time motion capture
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Augmented sport: exploring collective user experience
Proceedings of the Virtual Reality International Conference: Laval Virtual
MotionDraw: a tool for enhancing art and performance using kinect
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Graph-based analysis of physical exercise actions
Proceedings of the 1st ACM international workshop on Multimedia indexing and information retrieval for healthcare
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In this work, we describe a novel system that automatically evaluates dance performances against a gold-standard performance and provides visual feedback to the performer in a 3D virtual environment. The system acquires the motion of a performer via Kinect-based human skeleton tracking, making the approach viable for a large range of users, including home enthusiasts. Unlike traditional gaming scenarios, when the motion of a user must by kept in synch with a pre-recorded avatar that is displayed on screen, the technique described in this paper targets online interactive scenarios where dance choreographies can be set, altered, practiced and refined by users. In this work, we have addressed some areas of this application scenario. In particular, a set of appropriate signal processing and soft computing methodologies is proposed for temporally aligning dance movements from two different users and quantitatively evaluating one performance against another.