Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object ModelReportar como inadecuado


Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model


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1

School of Mechanical and Aerospace Engineering, Nanyang Technological University NTU, 50 Nanyang Avenue, Singapore 639798, Singapore

2

ST Engineering-NTU Corporate Laboratory, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore





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Author to whom correspondence should be addressed.



Academic Editor: Felipe Gonzalez Toro

Abstract In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle UAV applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algorithm initially finds feature correspondences in a way that an improved binary descriptor is developed for global feature matching and an iterative Lucas–Kanade optical flow algorithm is employed for local feature tracking. The second main module is the use of an efficient local geometric filter LGF, which handles outlier feature correspondences based on a new forward-backward pairwise dissimilarity measure, thereby maintaining pairwise geometric consistency. In the proposed LGF module, a hierarchical agglomerative clustering, i.e., bottom-up aggregation, is applied using an effective single-link method. The third proposed module is a heuristic local outlier factor to the best of our knowledge, it is utilized for the first time to deal with outlier features in a visual tracking application, which further maximizes the representation of the target object in which we formulate outlier feature detection as a binary classification problem with the output features of the LGF module. Extensive UAV flight experiments show that the proposed visual tracker achieves real-time frame rates of more than thirty-five frames per second on an i7 processor with 640 × 512 image resolution and outperforms the most popular state-of-the-art trackers favorably in terms of robustness, efficiency and accuracy. View Full-Text

Keywords: unmanned aerial vehicle; visual object tracking; reliable global-local model; local geometric filter; local outlier factor; robust real-time performance unmanned aerial vehicle; visual object tracking; reliable global-local model; local geometric filter; local outlier factor; robust real-time performance





Autor: Changhong Fu 1,2, Ran Duan 1,2, Dogan Kircali 1,2 and Erdal Kayacan 1,*

Fuente: http://mdpi.com/



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