基于时空显著性建模的空中飞行器跟踪方法

doi:10.7527/S1000-6893.2019.23388

Abstract

Abstract: This paper studies the robust visual tracking problem of airborne aircraft in complex environments. To improve the robustness in tracking airborne targets against challenging factors like target deformation, aspect ratio variation, and complex background, this paper models the saliency characteristics of the independent objects in the tracking scene and builds a more accurate target representation model. Different from traditional single-frame saliency detection methods, this paper proposes a spatio-temporal saliency estimation model, which makes use of prior knowledge of the target provided by the tracking algorithm and multi-frame observation data. The estimated saliency map is used to select of effective visual features and build accurate target representation in the tracking algorithm, which reduces the interference of the background clutter. Experimental results show that the proposed method provides an effective solution to the above problems in airborne tracking tasks and outperforms most state-of-the-art methods in accuracy and robustness. Moreover, the method shows excellent performance in tracking other objects.

Key words: visual tracking, airborne, target representation model, saliency estimation, spatio-temporal model, Bayesian inference

CLC Number:

V249
TP391

ZHANG Weijun, ZHONG Sheng, WANG Jianhui. Airborne target tracking based on spatio-temporal saliency modeling[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(3): 323388-323388.

References 39

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Airborne target tracking based on spatio-temporal saliency modeling

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