A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos
1
Department Electronics and Informatics, AVSP Lab, Vrije Universiteit Brussels, 1050 Brussels, Belgium
2
School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, China
3
Interuniversity Microelectronics Center, 3001 Leuven, Belgium
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(9), 1347; https://doi.org/10.3390/rs10091347
Received: 13 July 2018
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Revised: 14 August 2018
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Accepted: 19 August 2018
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Published: 23 August 2018
Multi-Object Tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, changes of size, appearance and motion of the moving objects and occlusions caused by the interaction between moving and static objects in the scene. To deal with these problems, this work proposes a four-stage hierarchical association framework for multiple object tracking in airborne video. The proposed framework combines Data Association-based Tracking (DAT) methods and target tracking using a compressive tracking approach, to robustly track objects in complex airborne surveillance scenes. In each association stage, different sets of tracklets and detections are associated to efficiently handle local tracklet generation, local trajectory construction, global drifting tracklet correction and global fragmented tracklet linking. Experiments with challenging airborne videos show significant tracking improvement compared to existing state-of-the-art methods.
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Keywords:
multiple object tracking; airborne video; tracklet confidence; hierarchical association framework
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Chen, T.; Pennisi, A.; Li, Z.; Zhang, Y.; Sahli, H. A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos. Remote Sens. 2018, 10, 1347. https://doi.org/10.3390/rs10091347
AMA Style
Chen T, Pennisi A, Li Z, Zhang Y, Sahli H. A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos. Remote Sensing. 2018; 10(9):1347. https://doi.org/10.3390/rs10091347
Chicago/Turabian StyleChen, Ting, Andrea Pennisi, Zhi Li, Yanning Zhang, and Hichem Sahli. 2018. "A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos" Remote Sensing 10, no. 9: 1347. https://doi.org/10.3390/rs10091347
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