Next Article in Journal
Quality Assessment of the Bidirectional Reflectance Distribution Function for NIR Imagery Sequences from UAV
Previous Article in Journal
Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data
Open AccessArticle

A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos

by 1,2,*, 1,3, 2, 2 and 1,2,3
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 / Revised: 14 August 2018 / Accepted: 19 August 2018 / 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. View Full-Text
Keywords: multiple object tracking; airborne video; tracklet confidence; hierarchical association framework multiple object tracking; airborne video; tracklet confidence; hierarchical association framework
Show Figures

Graphical abstract

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.

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.

Chicago/Turabian Style

Chen, Ting; Pennisi, Andrea; Li, Zhi; Zhang, Yanning; Sahli, Hichem. 2018. "A Hierarchical Association Framework for Multi-Object Tracking in Airborne Videos" Remote Sens. 10, no. 9: 1347.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop