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Weighted Method for 3D-Point Reconstruction in Multi-Vision System

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This paper proposes a weighted method for 3D-Point Reconstruction in a multi-vision system. For the feet of common perpendicular of two corresponding Back-Projection Lines are closed to the actual position of this 3D-Point, the method takes every foot as a measurement of the 3D-Point. Furthermore, a multi-vision system can measure a 3D-Point several times by several feet. Therefore, the method adjusts the weights of these perpendicular feet to find a better estimation for 3D-Point Reconstruction. The weight-adjusting algorithm based on Error Propagation Rule predicts the errors of Back-Projection Lines which reflect the impact of different cameras on 3D-Point Reconstruction, and then sets the weight of each perpendicular foot according to errors of the two relevant Back-Projection Lines. This method has a clear physical meaning and is relatively easy to be implemented in multi-vision systems. Experiments show that this method is better than traditional optimization algorithms both in accuracy and computational cost.
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Document Type: Research Article

Publication date: 2012-05-01

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