An Approach to Automatic Great-Scene 3D Reconstruction Based on UAV Sequence Images

Zi Ming Xiong; Gang Wan

doi:10.4028/www.scientific.net/AMM.229-231.2294

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 229-231An Approach to Automatic Great-Scene 3D...

An Approach to Automatic Great-Scene 3D Reconstruction Based on UAV Sequence Images

Abstract:

In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence images. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieving images match; quasi-perspective projection model and factorization is employed to calibrate the uncalibrated image sequences automatically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi-dense diffusing algorithm is bestowed to make 3D point denseness; the algorithm of bundle adjustment is taken to improve the precision of 3D points; the approach of Possion surface reconstruction is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.

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Periodical:

Applied Mechanics and Materials (Volumes 229-231)

Pages:

2294-2297

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.229-231.2294

Citation:

Cite this paper

Online since:

November 2012

Authors:

Zi Ming Xiong, Gang Wan

Keywords:

3D Optimization, 3D Reconstruction, Feature Match, Possion Surface Reconstruction, UAV

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