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RI | Publications | Long-term motion estimation from images
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Long-term motion estimation from images
D. Strelow and S. Singh
In Proceedings, International Symposium on Experimental Robotics, July, 2006.
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| Abstract |
Cameras are promising sensors for estimating the motion of autonomous vehicles without GPS and for automatic scene modeling. Furthermore, a wide variety of shape-from-motion algorithms exist for simultaneously estimating the camera's six degree of freedom motion and the three-dimension structure of the scene, without prior assumptions about the camera's motion or an existing map of the scene. However, existing shape-from-motion algorithms do not address the problem of accumulated long-term drift in the estimated motion and scene structure, which is critical in autonomous vehicle applications. The paper introduces a proof of concept system that exploits a new tracker, the variable state dimension filter (VSDF), and SIFT keypoints to recognize previously visited locations and limit drift in long-term camera motion estimates. The performance of this system on an extended image sequence is described.
| Notes |
Associated center: FRC
Number of pages: 10
| Text Reference |
D. Strelow and S. Singh, "Long-term motion estimation from images," In Proceedings, International Symposium on Experimental Robotics, July, 2006.
| BibTeX Reference |
@inproceedings{Strelow_2006_5537,
author = "Dennis Strelow and Sanjiv Singh",
title = "Long-term motion estimation from images",
booktitle = "In Proceedings, International Symposium on Experimental Robotics",
month = "July",
year = "2006"
}