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Proceedings Paper

Camera motion estimation using normal flows
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Paper Abstract

An autonomous system must have the capability of estimating or controlling its own motion parameters. There already exit tens of research work to fulfill the task. However, most of them are based on the motion correspondences establishment or full optical flows estimation. The above solutions put restrictions on the scene: either there must be presence of enough distinct features, or there must be dense texture. Different from the traditional works, utilizing no motion correspondences or epipolar geometry, we start from the normal flow data, ensure good use of every piece of them because they could only be sparsely available. We apply the spherical image model to avoid the ambiguity in describing the camera motion. Since each normal flow gives a locus for the location of the camera motion, the intersection of such loci offered by different data points will narrow the possibilities of the camera motion and even pinpoint it. A voting scheme in φ-θ domain is applied to simplify the 3D voting space to a 2D voting space. We tested the algorithms introduced above by using both synthetic image data and real image sequences. Experimental results are shown to illustrate the potential of the methods.

Paper Details

Date Published: 20 March 2013
PDF: 5 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87681W (20 March 2013); doi: 10.1117/12.2010851
Show Author Affiliations
Ding Yuan, BeiHang Univ. (China)
Miao Liu, BeiHang Univ. (China)
Hong Zhang, BeiHang Univ. (China)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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