Improving of GPS localization by 3D vision

基于GPS的定位在高层建筑或干扰(如一些电子设备)附近往往效果不佳。这 这项研究的目的是通过分析从绑定到 GPS传感器。这项研究对无人机(UAV)特别有用，无人机主要依靠 GPS用于定位，还经常配备数码相机。3D计算机视觉算法可以恢复 摄像机根据其记录的视频帧进行的3D运动。这些算法提供了一个位置 独立于GPS的测量。通过融合这两个位置测量，我们可以改进 GPS读数的准确性和一致性。当卫星图像可用时，计算机视觉算法 允许我们将运动轨迹记录到卫星地图上，以进一步增强位置可靠性。这 将与致力于无人机应用的当地公司MDA进行研究，以加强他们的 产品和服务。

GPS-based positioning is often poor near high buildings or interferences such as some electronic devices. This research aims to enhance GPS position accuracy by analyzing a video captured from a camera bound to the GPS sensor. This research is particularly useful for unmanned aerial vehicles (UAVs), which mainly rely on GPS for positioning and also often equipped with digital cameras. 3D computer vision algorithms can recover the 3D motion of a video camera from its recorded video frames. These algorithms provide a position measurement independent of that from GPS. By fusing these two position measurements, we can improve the accuracy and coherency of GPS readings. When a satellite image is available, computer vision algorithms allow us to register the motion trajectory to the satellite map to further enhance position reliability. This research will be carried out with MDA, a local company dedicated in UAV applications, to strengthen their products and services.