Visual-Inertial Ego-Positioning for Flying Cameras

In this paper, a low cost monocular camera and an inertial measurement unit (IMU) are combined for the ego-positioning on flying cameras. We firstly survey the state-of-the-art monocular visual positioning approaches, such as Simultaneous Localization and Mapping (SLAM) and Model-Based Localization (MBL). Three of the most representative methods including ORB-SLAM, LSD-SLAM, and MBL， which are originally designed for vehicles, are evaluated in different scenarios. Based on the experiment results, we analyze the pros and cons of each method. Considering the limitations of vision-only approaches, we fuse the visual positioning with an inertial sensor based on a loosely-coupled framework. The experiment results demonstrate the benefits of visual-inertial sensor fusion.