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Incremental Fusion of Structure-from-Motion and GPS Using Constrained Bundle Adjustments

机译:利用约束束调整增量调整动感结构和GPS的融合

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Two problems occur when bundle adjustment (BA) is applied on long image sequences: large calculation time and drift (or error accumulation). In recent work, the calculation time is reduced by local BAs applied in an incremental scheme. The drift may be reduced by fusion of GPS and Structure-from-Motion. An existing fusion method is BA minimizing a weighted sum of image and GPS errors. This paper introduces two constrained BAs for fusion which enforce an upper bound for the reprojection error. These BAs are alternatives to the existing fusion BA which does not guarantee a small reprojection error and requires a weight as input. Then, the three fusion BAs are integrated in an incremental Structure-from-Motion method based on local BA. Last, we will compare the fusion results on long monocular image sequences and low cost GPS.
机译:将束调整(BA)应用于长图像序列时,会出现两个问题:计算时间长和漂移(或误差累积)。在最近的工作中,通过在增量方案中应用本地BA减少了计算时间。可以通过融合GPS和动态结构来减少漂移。现有的融合方法是BA最小化图像和GPS错误的加权和。本文介绍了两个用于融合的约束BA,它们对重投影误差施加了上限。这些BA是现有融合BA的替代,它不能保证较小的重投影误差,并且需要权重作为输入。然后,将三个融合BA集成到基于本地BA的增量动感结构方法中。最后,我们将比较长单眼图像序列和低成本GPS上的融合结果。

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