Toward natural interaction in the real world: real-time gesture recognition
Name
icmi2010_yingyin.pdf
Size
4.41 MB
Format
Adobe PDF
Checksum (MD5)
4f40f92add5b99489fa7e7134e065066
Author(s)
Yin, Ying
Davis, Randall
Date Issued
November 2010
Journal
Proceeding of the International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction (ICMI-MLMI '10)
Publisher
Association for Computing Machinery (ACM)
Citation
Yin, Ying, and Randall Davis. “Toward natural interaction in the real world.” ACM Press, 2010.
Version
Author's final manuscript
Abstract
Using a new hand tracking technology capable of tracking 3D hand postures in real-time, we developed a recognition system for continuous natural gestures. By natural gestures, we mean those encountered in spontaneous interaction, rather than a set of artificial gestures chosen to simplify recognition. To date we have achieved 95.6% accuracy on isolated gesture recognition, and 73% recognition rate on continuous gesture recognition, with data from 3 users and twelve gesture classes. We connected our gesture recognition system to Google Earth, enabling real time gestural control of a 3D map. We describe the challenges of signal accuracy and signal interpretation presented by working in a real-world environment, and detail how we overcame them.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/1891903.1891924
