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Robust Self-calibration from Single Image Using RANSAC

机译:使用Ransac从单个图像中校准的鲁棒自校准

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In this paper, a novel approach for the self-calibration of single image is proposed. Unlike most existing methods, we can obtain the intrinsic and extrinsic parameters based on the information of restricted image points from single image. First, we show how the vanishing point, vanishing line and foot-to-head plane homology can be used to obtain the calibration parameters and then we show our approach how to efficiently adopt RANSAC to estimate them. In addition, noise reduction is proposed to handle the measurement uncertainties of input points. Results in synthetic and real scenes are presented to evaluate the performance of the proposed method.
机译:本文提出了一种用于单幅图像自校准的新方法。与大多数现有方法不同,我们可以基于来自单个图像的受限图像点的信息获得内在和外在参数。首先,我们展示了消失点,消失线和脚到头平面同源如何用于获得校准参数,然后我们展示了我们的方法如何有效地采用Ransac来估算它们。此外,提出了降噪来处理输入点的测量不确定性。提出了合成和实场景的结果,以评估所提出的方法的性能。

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