A Comparison of Optical Flow algorithms for Real Time Aircraft Guidance and Navigation
Marco Mammarella, Giampiero Campa, Mario Luca Fravolini, Yu Gu, Brad A. Seanor, Marcello Napolitano · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2008
This paper focuses on the analysis of the performance of several optical flow algorithms for application within aeronautic applications such as obstacle detection and collision avoidance for lightweight unmanned aerial vehicles (UAVs). The study involved the comparison of nine different optical flow algorithms. Some of these algorithms were developed at West Virginia University (WVU); some were included in the Video and Image Processing Blockset ® of Matlab ® while others were available for download from different sources. The comparative study was performed using both a number of different real-world videos with images rotating or translating at known speeds and a Virtual Reality Environment (VRE) where an aircraft performs complex maneuvers into a detailed virtual world. The comparison of the Optical Flow (OF) algorithms is provided in terms of accuracy of estimation, and an analysis of the computational effort required by the different algorithms was also performed. As expected, algorithms belonging to common conceptual classes turn out to have similar strengths and weaknesses. However, when the computational requirements are taken into account, there is no clear “winning” algorithm, therefore suggesting that ultimately the selection of the “best” algorithm is has to be driven by the particular application.