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Exploiting SLAM to improve feature matching

机译:利用SLAM改善功能匹配

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摘要

One of the main problems associated with vision-based SLAM is the difficulty to find high-quality and indistinguishable landmarks which are detectable across significant viewpoint changes. Most of the current visual SLAM systems utilize the feature extraction methods that have been proposed for the offline computer vision tasks, which are either too slow for a real-time SLAM or not robust enough against viewpoint changes. In this paper, we demonstrate that by incorporating the position information of the robot into the feature description, we can help the feature matching process significantly.
机译:与基于视觉的SLAM相关的主要问题之一是难以找到在明显的视点变化中可检测到的高质量且难以区分的地标。当前的大多数视觉SLAM系统都使用针对脱机计算机视觉任务建议的特征提取方法,这些方法对于实时SLAM而言太慢,或者对于视点更改而言不够鲁棒。在本文中,我们证明了通过将机器人的位置信息纳入特征描述中,可以显着帮助特征匹配过程。

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