Cross-correlation-based robust object tracking in aerial videos

Paper


Perera, Asanka G, Law, Yee Wei and Chahl, Javaan. 2019. "Cross-correlation-based robust object tracking in aerial videos." 18th Australian International Aerospace Congress (AIAC18). Melbourne, Australia 24 - 26 Feb 2019 Australia .
Paper/Presentation Title

Cross-correlation-based robust object tracking in aerial videos

Presentation TypePaper
AuthorsPerera, Asanka G, Law, Yee Wei and Chahl, Javaan
Journal or Proceedings TitleProceedings of the 18th Australian International Aerospace Congress (AIAC18)
Journal Citationpp. 222-228
Number of Pages7
Year2019
Place of PublicationAustralia
ISBN9781925627213
Web Address (URL) of Paperhttps://search.informit.org/doi/10.3316/informit.321573522790602
Web Address (URL) of Conference Proceedingshttps://search.informit.org/doi/10.3316/INFORMIT.9781925627213
Conference/Event18th Australian International Aerospace Congress (AIAC18)
Event Details
18th Australian International Aerospace Congress (AIAC18)
Parent
Australian International Aerospace Congress
Delivery
In person
Event Date
24 to end of 26 Feb 2019
Event Location
Melbourne, Australia
Abstract

Normalized cross-correlation (NCC) is a well-known technique in visual feature tracking. However, it is sensitive to the scale, rotation and warping differences in the target object. In this work, we propose a method to use with the NCC filter for rotation- and scale-invariant object tracking. The proposed solution consists of three modules: (i) multiple appearance generation in the search image at different rotation angles and scales, (ii) bounding box drift correction by a re-initialization step, and (iii) failure handling by tracker combination. A point tracker that uses the Kanade-Lucas-Tomasi feature-tracking algorithm and a histogram-based tracker that uses the continuously adaptive mean shift (CAMShift) algorithm are used as supporting trackers. A "Faster R-CNN" detector is used to adjust the estimated bounding boxes. The proposed combined tracker is evaluated using the VisDrone2018 and VOT2018 datasets and compared with five recently published trackers.

KeywordsAerial video; scale-invariant; rotation-invariant; normalized cross-correlation; object tracking
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 20204007. Control engineering, mechatronics and robotics
Public Notes

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Byline AffiliationsUniversity of South Australia
Defence Science and Technology Group, Australia
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