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Online multi-object tracking with efficient track drift and fragmentation handling
Journal article   Open access   Peer reviewed

Online multi-object tracking with efficient track drift and fragmentation handling

Jaeyong Ju, Daehun Kim, Bonhwa Ku, David K. Han and Hanseok Ko
Journal of the Optical Society of America. A, Optics, image science, and vision, v 34(2), pp 280-293
01 Feb 2017
PMID: 28157856
url
https://doi.org/10.1364/JOSAA.34.000280View
Published, Version of Record (VoR) Restricted

Abstract

Optics Physical Sciences Science & Technology
This paper addresses the problem of multi-object tracking in complex scenes by a single, static, uncalibrated camera. Tracking-by-detection is a widely used approach for multi-object tracking. Challenges still remain in complex scenes, however, when this approach has to deal with occlusions, unreliable detections (e.g., inaccurate position/ size, false positives, or false negatives), and sudden object motion/appearance changes, among other issues. To handle these problems, this paper presents a novel online multi-object tracking method, which can be fully applied to real-time applications. First, an object tracking process based on frame-by-frame association with a novel affinity model and an appearance update that does not rely on online learning is proposed to effectively and rapidly assign detections to tracks. Second, a two-stage drift handling method with novel track confidence is proposed to correct drifting tracks caused by the abrupt motion change of objects under occlusion and prolonged inaccurate detections. In addition, a fragmentation handlingmethod based on a track-to-track association is proposed to solve the problem in which an object trajectory is broken into several tracks due to long-term occlusions. Based on experimental results derived from challenging public data sets, the proposed method delivers an impressive performance compared with other state-of-the-art methods. Furthermore, additional performance analysis demonstrates the effect and usefulness of each component of the proposed method. (C) 2017 Optical Society of America

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Collaboration types
International collaboration
Web of Science research areas
Optics
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