Motion-based control is gaining popularity, and motion gestures form a complementary modality in human-computer interactions. To achieve more robust userindependent motion gesture recognition in a manner analogous to automatic speech recognition, we need a deeper understanding of the motions in gesture, which arouses the need for a 6D motion gesture database. Presented database contains comprehensive motion data, including the position, orientation, acceleration, and angular speed, for a set of common motion gestures performed by different users. This motion gesture database can be a useful platform for researchers and developers to build their recognition algorithms as well as a common test bench for performance comparisons.
The files are available for download via HTTP. Link: http://web.cs.wpi.edu/~claypool/mmsys-dataset/2012/6dmg/ Dataset can be downloaded in one ZIP file: Link: http://web.cs.wpi.edu/~claypool/mmsys-dataset/2012/6dmg/MotionGesture_042511.rar Dataset mirror is available: http://www.ece.gatech.edu/6DMG/6DMG.html
References and Citation
Use of the datasets in published work should be acknowledged by a full citation to the paper [CAJ12] at the MMSys conference ( MMSys 12, February 22-24, Chapel Hill, North Carolina, USA, Copyright 2012 ACM 978-1-4503-1131-1/12/02).
CAJ12: M. Chen, G. AlRegib, B. Juang, 6DMG: A New 6D Motion Gesture Database, Proceedings of the Second ACM Multimedia Systems Conference (MMSys), Chapel Hill, NC, USA, February 22-24, 2012.