Abstract
A local map module is often implemented in modern VO/VSLAM systems to improve data association and pose estimation. Conventionally, the local map contents are determined by co-visibility. While co-visibility is cheap to establish, it utilizes the relatively-weak temporal prior (i.e. seen before, likely to be seen now), therefore admitting more features into the local map than necessary. This paper describes an enhancement to co-visibility local map building by incorporating a strong appearance prior, which leads to a more compact local map and latency reduction in downstream data association. The appearance prior collected from the current image influences the local map contents: only the map features visually similar to the current measurements are potentially useful for data association. To that end, mapped features are indexed and queried with Multi-index Hashing (MIH). An online hash table selection algorithm is developed to further reduce the query overhead of MIH and the local map size. The proposed appearance-based local map building method is integrated into a state-of-the-art VO/VSLAM system. When evaluated on two public benchmarks, the size of the local map, as well as the latency of real-time pose tracking in VO/VSLAM are significantly reduced. Meanwhile, the VO/VSLAM mean performance is preserved or improves.
Abstract (translated)
在现代的VO/VSLAM系统中，为了提高数据关联性和姿态估计，通常采用局部映射模块。传统上，局部地图的内容是由共可见性决定的。虽然共视性的建立成本很低，但它利用了相对较弱的时间先验（即以前看到过，现在可能看到），因此在局部地图中引入了比需要更多的特征。本文介绍了一种通过引入强外观先验增强局部地图共可见性的方法，从而使下游数据关联的局部地图更加紧凑，延迟减少。从当前图像收集的外观会影响本地地图内容：只有视觉上类似于当前测量的地图功能才可能对数据关联有用。为此，使用多索引散列（MIH）对映射的特性进行索引和查询。为了进一步降低MIH的查询开销和局部地图大小，提出了一种在线哈希表选择算法。提出的基于外观的局部地图构建方法集成到最先进的VO/VSLAM系统中。当在两个公共基准上进行评估时，本地地图的大小以及VO/VSLAM中实时姿态跟踪的延迟都显著减少。同时，保持或提高了VO/VSLAM的平均性能。
URL
https://arxiv.org/abs/1905.07797
