Publication
Title
Explaining and verifying the robustness of visual object trackers to noise
Author
Abstract
2D tracking is an important computer vision task with important applications in autonomous embedded systems such as Unmanned Aerial Vehicles and autonomous cars that particularly attracted scientists in the past few years. Many new methods have aroused that significantly pushed the stateof-the-art performance in terms of tracking precision, success rate and execution speed, in well-designed and established existing publicly available benchmarks. Despite the fact that these benchmark datasets include as many application scenarios as possible, another commonly neglected yet important aspect is the robustness of tracking methods, notably to noise related with image acquisition, capturing storing and transmission. This paper presents a robustness evaluation toolkit for 2D Visual Object Tracking, that can exploit existing datasets in order to evaluate the robustness of 2D visual tracking methods to realistic image distortion scenarios, mostly encountered in embedded systems. The source code of this toolkit will be made publicly available upon paper acceptance.
Language
English
Source (book)
2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 26-29 June, 2022, Nafplio, Greece
Publication
New york : 2022
ISBN
978-1-6654-7822-9
DOI
10.1109/IVMSP54334.2022.9816343
Volume/pages
(2022) , 5 p.
ISI
000853856800063
Full text (Publisher's DOI)
UAntwerpen
Publication type
Subject
External links
Web of Science
Record
Identifier
Creation 17.10.2023
Last edited 17.06.2024
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