Monocular Visual-IMU Odometry: A Comparative Evaluation of Detector-Descriptor-Based Methods
Monocular Visual-IMU Odometry: A Comparative Evaluation of Detector-Descriptor-Based Methods
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DOI：
10.1109/tits.2019.2919003
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发表时间：
2020-06-01
影响因子：
8.5
通讯作者：
Zhou, Huiyu
中科院分区：
文献类型：
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作者：
Dong, Xingshuai;Dong, Xinghui;Zhou, Huiyu
单目视觉惯性测量单元（IMU）里程计在各种智能车辆中得到了广泛的应用。作为一种流行的技术，基于检测器描述符的视觉IMU里程计是有效的和高效的，由于事实上，本地描述符是强大的对遮挡，背景杂波，和突然的内容变化。然而，据我们所知，有没有一个全面的和比较的性能评价研究的不同组合的检测器和描述符最近开发的。为了弥补这一差距，我们在一个统一的框架内进行这样的比较研究。特别地，从著名的KITTI数据集中选择了六条具有不同长度、形状和道路场景的典型路线。我们首先评估的性能的不同组合的显著点检测器和本地描述符使用的六条路线。然后，我们调整每个路由获得的最佳检测器或描述符的参数，以进一步增强结果。本文不仅为评估各种算法提供了全面的基准，而且为开发处理不同道路场景的检测器和描述符提供了指导性的指导方针和见解。
Monocular visual-inertial measurement unit (IMU) odometry has been widely used in various intelligent vehicles. As a popular technique, detector-descriptor-based visual-IMU odometry is effective and efficient due to the fact that local descriptors are robust against occlusions, background clutter, and abrupt content changes. However, to our knowledge, there is not a comprehensive and comparative evaluation study on the performance of different combinations of detectors and descriptors recently developed. In order to bridge this gap, we conduct such a comparative study in a unified framework. In particular, six typical routes with different lengths, shapes, and road scenes are selected from the well-known KITTI dataset. We first evaluate the performance of different combinations of salient point detectors and local descriptors using the six routes. Then, we tune the parameters of the best detector or descriptor obtained for each route, to further augment the results. This paper provides not only comprehensive benchmarks for assessing various algorithms but also instructive guidelines and insights for developing detectors and descriptors to handle different road scenes.