Journal
SENSORS
Volume 18, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/s18092751
Keywords
UAV video; visual tracking; correlation filter; cellular automata; adaptive appearance model
Funding
- National Key Research and Development Program [2016YFB0502502]
- Foundation Project for Advanced Research Field [614023804016HK03002]
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With the increasing availability of low-cost, commercially available unmanned aerial vehicles (UAVs), visual tracking using UAVs has become more and more important due to its many new applications, including automatic navigation, obstacle avoidance, traffic monitoring, search and rescue, etc. However, real-world aerial tracking poses many challenges due to platform motion and image instability, such as aspect ratio change, viewpoint change, fast motion, scale variation and so on. In this paper, an efficient object tracking method for UAV videos is proposed to tackle these challenges. We construct the fused features to capture the gradient information and color characteristics simultaneously. Furthermore, cellular automata is introduced to update the appearance template of target accurately and sparsely. In particular, a high confidence model updating strategy is developed according to the stability function. Systematic comparative evaluations performed on the popular UAV123 dataset show the efficiency of the proposed approach.
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