Fundamental matrix estimation for binocular vision measuring system used in wild field

Nian Yan; Xiangjun Wang; Feng Liu

doi:10.1117/12.2070319

24 November 2014 Fundamental matrix estimation for binocular vision measuring system used in wild field

Nian Yan, Xiangjun Wang, Feng Liu

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93010S (2014) https://doi.org/10.1117/12.2070319
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

A method has been proposed to estimate the fundamental matrix of a positing and monitoring binocular vision system with a long working distance and a large field of view. Because of the long working distance and large field of view, images grabbed by this system are seriously blurred, leading to a lack of local features. The edge points are acquired using the Canny algorithm firstly, then the pre-matched points are obtained by the GMM-based points sets registration algorithm, and eventually the fundamental matrix are estimated using the RANSAC algorithm. In actual application, two cameras are 2km away from the object, the fundamental matrix are figured out, and the distance between each point and the corresponding epipolar line is less than 0.8 pixel. Repeated experiments indicate that the average distances between the points and the corresponding epipolar lines are all within 0.3 pixel and the deviations of the distances are all within 0.3 pixel too. This method takes full advantage of the edges in the environment and does not need extra control points, whats more, it can work well in low SNR images.

Citation Download Citation

Nian Yan, Xiangjun Wang, and Feng Liu "Fundamental matrix estimation for binocular vision measuring system used in wild field", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010S (24 November 2014); https://doi.org/10.1117/12.2070319

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