Abstract
Object tracking for unmanned aerial vehicle applications in outdoor scenes is a very complex problem. In videos captured by unmanned aerial vehicle, due to frequent variation in illumination, motion blur, image noise, deformation, lack of image texture, occlusion, fast motion, and other degradations, most tracking methods will lead to failure. The article focuses on the object tracking in severely degraded videos. To deal with those various degradations, a real-time object tracking method for high dynamic background is developed. By integrating histogram of oriented gradient, RGB histogram and motion histogram into a novel statistical model, our method can robustly track the target in unmanned aerial vehicle captured videos. Compared to those existing methods, our proposed approach costs less resource in the tracking, significantly increases the tracking speed, and runs faster than state-of-the-art methods. Also, our approach achieved satisfactory tracking results on the challenging visual tracking benchmark, object tracking benchmark 2013, the supplementary experiments demonstrates that our method is more effective and accurate than other methods.
Highlights
During the last 10 years, people witnessed the emergence of notable development in the technology and application of unmanned aerial vehicles (UAV)
The flight security will be a significant issue in the future, the UAV must have the ability to sense its surroundings during the flight
0.5 0.15 0.01 0.04 0.20 sequences captured by UAV often possess severe degradations, as shown in Figure 6, and according to the optical flow the motion in the frame is very severe
Summary
During the last 10 years, people witnessed the emergence of notable development in the technology and application of unmanned aerial vehicles (UAV). With the abundant informations provided by the vision system, a drone can detect hidden military threats and take the appointed action This technology has aroused lots of attention in the recent 10 years. For common object tracking methods, the motion blur, camera rotation, and fast motion is quite challenging to achieve high quality tracking result for the UAV captured video because it does not do further processing for the degradation information. Those previously proposed trackers are seldom specialized to handle degradations like motion blur and fast motion. The rest of the article is organized as follows: the related work on object tracking is briefly and systematically reviewed in “Related works” section; in “The proposed approach” section, we present a detailed description of the proposed algorithm; and in “Experiments” section, we give out the quantitative and qualitative experiments’ results, some of the limitations of our approach is discussed; and the conclusion of this article is bring out in the last section
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