Aerial Image Mosaicing Approach Based on Feature Matching

The paper treats a problem of building an image mosaic or a 2D map from the sequence of images taken by an Unmanned Aerial Vehicle (UAV). The proposed algorithm is composed of the following parts: feature detection and extraction using Speeded Up Robust Features (SURF) descriptor, feature matching using Fast Approximate Nearest Neighbor Search (FANN) with automatic algorithm configuration, estimation of the optimal transform between images using RANdom SAmple Consensus (RANSAC) and finally creating a mosaic by stitching images together using the obtained transformations. Summarizing results obtained in two different scenarios, it can be concluded that the proposed algorithm exhibits near real time performance for automated UAV 2D aerial mapping.