3D Mapping and Localization on Aerial Images

Fast and accurate observation of an area in disaster scenarios such as earthquake, flood and avalanche is crucial for first aid teams. Digital surface models, orthomosaics and object detection algorithms can play an important role in rapid decision making and response. In recent years, Unmanned Aerial Vehicles (UAVs) have become increasingly popular because of their ability to perform tasks at lower costs. A real-time orthomosaic generated by using UAVs can help in tasks where both speed and efficiency are required. An orthomosaic provides an overview of the area to be observed and helps the operator to find the regions of interest, and object detection algorithms helps to localize objects of interest in those regions. In this study, a monocular SLAM based mapping and detection system has been developed which combines the camera and GPS data of the UAV. The performance of the developed method is evaluated in both single and multiple UAVs scenario.