Efficient Road Detection and Tracking for Unmanned Aerial Vehicle


An unmanned aerial vehicle (UAV) has many applications in a very selection of fields. Detection and tracking of a selected road in UAV videos play an vital role in automatic UAV navigation, traffic monitoring, and ground-vehicle tracking, and also is terribly useful for constructing road networks for modeling and simulation. In this paper, an efficient road detection and tracking framework in UAV videos is proposed. In explicit, a graph-cut-primarily based detection approach is given to accurately extract a specified road region during the initialization stage and in the middle of tracking method, and a fast homography-based mostly road-tracking scheme is developed to automatically track road areas. The high potency of our framework is attributed to two aspects: the road detection is performed solely when it's necessary and most work in locating the road is rapidly done via terribly fast homography-based mostly tracking. Experiments are conducted on UAV videos of real road scenes we tend to captured and downloaded from the Internet. The promising results indicate the effectiveness of our proposed framework, with the precision of ninety eight.4p.c and processing 34 frames per second for 1046 × 595 videos on average.

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