Global motion-aware robust visual object tracking for electro optical targeting systems

Kim, Byeong Hak (author), Lukežič, Alan (author), Lee, Jong Hyuk (author), Jung, Ho Min (author), Kim, Min Young (author)

Although recently developed trackers have shown excellent performance even when tracking fast moving and shape changing objects with variable scale and orientation, the trackers for the electro-optical targeting systems (EOTS) still suffer from abrupt scene changes due to frequent and fast camera motions by pan-tilt motor control or dynamic distortions in field environments. Conventional context aware (CA) and deep learning based trackers have been studied to tackle these problems, but they have the drawbacks of not fully overcoming the problems and dealing with their computational burden. In this paper, a global motion aware method is proposed to address the fast camera motion issue. The proposed method consists of two modules: (i) a motion detection module, which is based on the change in image entropy value, and (ii) a background tracking module, used to track a set of features in consecutive images to find correspondences between them and estimate global camera movement. A series of experiments is conducted on thermal infrared images, and the results show that the proposed method can significantly improve the robustness of all trackers with a minimal computational overhead. We show that the proposed method can be easily integrated into any visual tracking framework and can be applied to improve the performance of EOTS applications.

• Language: English
• Keywords: visual object tracking, camera motion, motion aware, robust tracking
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: 20 str.
• Numbering: Vol. 20, iss. 2, art. 566
• PID: 20.500.12556/RUL-133086
• UDC: 004.93
• ISSN on article: 1424-8220
• DOI: 10.3390/s20020566
• COBISS.SI-ID: 1538564547
• Publication date in RUL: 11.11.2021

Record is a part of a journal

• Title: Sensors
• Shortened title: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 20.01.2020

Secondary language

• Language: Slovenian
• Keywords: vizualno sledenje objektov, gibanje kamere, robustno vizualno sledenje