Fast Timeline Based Multi Object Online Tracking

IF 1.1 Q3 TRANSPORTATION SCIENCE & TECHNOLOGY Transport and Telecommunication Journal Pub Date : 2023-02-01 DOI:10.2478/ttj-2023-0007
Martin Hünermund, Maik Groneberg, Nils Brauckmann
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引用次数: 0

Abstract

Abstract Fast state-of-the-art multi-object-tracking (MOT) schemes, such as reported in challenges MOT16 and Mot20, perform tracking on a single sensor, often couple tracking and detection, support only one kind of object representation or don’t take varying latencies and update rates into account. We propose a fast generic MOT system for use in real world applications which is capable of tracking objects from different sensor / detector types with their respective latencies and update rates. An SORT inspired online tracking scheme is extended by time awareness using timelines as unifying concept. The system supports different object, sensor and filter and tracking types by modularizing and generalizing the online tracking scheme, while ensuring high performance using an efficient data-oriented C++-template-based implementation. Using the proposed system we achieve, with comparable evaluation metrics, framerates up to ten times higher than the fastest MOT schemes publicly listed for the axis-aligned bounding-box tracking challenges MOT17 and MOT20.
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基于快速时间轴的多目标在线跟踪
在挑战MOT16和Mot20中报道的最先进的快速多目标跟踪(MOT)方案,在单个传感器上执行跟踪,通常是耦合跟踪和检测,仅支持一种目标表示或不考虑不同的延迟和更新速率。我们提出了一个快速通用的MOT系统,用于现实世界的应用,它能够跟踪来自不同传感器/探测器类型的物体,具有各自的延迟和更新速率。以时间线为统一概念,对一种受SORT启发的在线跟踪方案进行了时间感知扩展。该系统通过模块化和泛化在线跟踪方案,支持不同的对象、传感器、滤波器和跟踪类型,同时使用高效的面向数据的基于c++模板的实现保证了高性能。使用所提出的系统,我们通过可比的评估指标,实现了比公开列出的最快的MOT方案高出10倍的帧率,用于轴向边界盒跟踪挑战MOT17和MOT20。
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来源期刊
Transport and Telecommunication Journal
Transport and Telecommunication Journal TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
3.00
自引率
0.00%
发文量
21
审稿时长
35 weeks
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