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2011
IEEE

Stable vision-aided navigation for large-area augmented reality

7 years 8 months ago
Stable vision-aided navigation for large-area augmented reality
In this paper, we present a unified approach for a drift-free and jitter-reduced vision-aided navigation system. This approach is based on an error-state Kalman filter algorithm using both relative (local) measurements obtained from image based motion estimation through visual odometry, and global measurements as a result of landmark matching through a pre-built visual landmark database. To improve the accuracy in pose estimation for augmented reality applications, we capture the 3D local reconstruction uncertainty of each landmark point as a covariance matrix and implicity rely more on closer points in the filter. We conduct a number of experiments aimed at evaluating different aspects of our Kalman filter framework, and show our approach can provide highly-accurate and stable pose both indoors and outdoors over large areas. The results demonstrate both the long term stability and the overall accuracy of our algorithm as intended to provide a solution to the camera tracking probl...
Taragay Oskiper, Han-Pang Chiu, Zhiwei Zhu, Supun
Added 22 Aug 2011
Updated 22 Aug 2011
Type Journal
Year 2011
Where VR
Authors Taragay Oskiper, Han-Pang Chiu, Zhiwei Zhu, Supun Samarasekera, Rakesh Kumar
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