Abstract:Image based Localization (IbL) uses both Structure from Motion (SfM) and Simultaneous Localization and Mapping (SLAM) data for accurate pose estimation. However, under conditions where there is a large perspective difference between the SfM images and SLAM keyframes, the SfM-SLAM co-visibility graph becomes sparse. As a result, the scale drift can increase especially when using monocular SLAM as part of the IbL framework. The drift rarely gets corrected at loop closure due to its large magnitude. We propose a … Show more
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