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Cooperative Visual Simultaneous Localization and Mapping by Ordering Keyframes Similarity

机译:通过排序关键帧相似度进行协作视觉同时定位和映射

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In this paper, multiple moving cameras, which are employed to build the maps individually, are integrated to construct a complete map of the whole large environment. Since multiple cameras may capture the same scenes during performing its own SLAM, the keyframes similarity of each cameras could be evaluated to construct the relation between the map of each camera. The proposed cooperative SLAM algorithm can efficiently build the complete map and reduce the computational time. Through the experiments and analyses on several environments with different size, the amount of feature points, and the size of overlapping area between cameras, the proposed cooperative SLAM with multiple moving cameras can efficiently obtain the information of moving cameras and the environments.
机译:在本文中,集成了用于分别构建地图的多个移动摄像机,以构建整个大型环境的完整地图。由于多个摄像机可能会在执行其自身的SLAM期间捕获相同的场景,因此可以评估每个摄像机的关键帧相似度,以构造每个摄像机的地图之间的关系。提出的协作式SLAM算法可以有效地构建完整的地图并减少计算时间。通过对具有不同大小,特征点数量以及摄像机之间重叠区域大小的几种环境进行实验和分析,提出的具有多个移动摄像机的协作SLAM可以有效地获取移动摄像机和环境的信息。

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