Advanced
Motion and Structure Estimation Using Fusion of Inertial and Vision Data for Helmet Tracker
Motion and Structure Estimation Using Fusion of Inertial and Vision Data for Helmet Tracker
International Journal of Aeronautical and Space Sciences. 2010. Mar, 11(1): 31-40
  • Published : March 01, 2010
Download
PDF
Export by style
Article
Author
Metrics
Cited by
About the Authors
Heo, Se-Jong
Shin, Ok-Shik
Park, Chan-Gook

Abstract
For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.
Keywords
View Fulltext