Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 13 July 2018 / Approved: 13 July 2018 / Online: 13 July 2018 (14:27:22 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Abstract

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, size, appearance and motion of the moving objects as well as occlusions due to the interaction between the moving objects and with other 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 (HATA). 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 video datasets show significant tracking improvement compared to existing state-of-art methods.

Keywords

Multiple object tracking; Airborne video; Tracklet confidence; Hierarchical association framework

Subject

Computer Science and Mathematics, Hardware and Architecture

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