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Recursive structure and motion estimation from noisy uncalibrated video sequences

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2 Author(s)
D. Q. Huynh ; School of Computer Science and Software Engineering, The University of Western Australia, AUSTRALIA ; A. Heyden

This paper builds on a novel framework of hybrid matching constraints for estimation of structure and recovery of camera focal length and motion, combining the advantages of both discrete and continuous methods. Our recursive method can deal with both image noise and outliers. The system is an extension of the epipolar hybrid matching constraints in conjunction with a simple structure estimation scheme using standard triangulation. The extension enables the system to deal with varying focal length of the camera. The structure obtained from some previous image frames is used to improve estimates of the camera focal length and motion for the current image frame. These are, in turn, used to refine the structure. Finally, a RANSAC outlier rejection scheme is employed to reject outlier tracks, inevitably obtained from any tracker. The performance of the proposed system is demonstrated on simulated experiments.

Published in:

Pattern Recognition, 2008. ICPR 2008. 19th International Conference on

Date of Conference:

8-11 Dec. 2008