Real-Time Inland CCTV Ship Tracking
Joint Authors
Hu, Zhongyi
Xu, Minghai
Xiao, Lei
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The predator algorithm is a representative pioneering work that achieves state-of-the-art performance on several popular visual tracking benchmarks and with great success when commercially applied to real-time face tracking in long-term unconstrained videos.
However, there are two major drawbacks of predator algorithm when applied to inland CCTV (closed-circuit television) ship tracking.
First, the LK short-term tracker within predator algorithm easily tends to drift if the target ship suffers partial or even full occlusion, mainly because the corner-points-like features employed by LK tracker are very sensitive to occlusion appearance change.
Second, the cascaded detector within the predator algorithm searches for candidate objects in a predefined scale set, usually including 3-5 elements, which hampers the tracker to adapt to the potential diverse scale variations of the target ship.
In this paper, we design a random projection based short-term tracker which can dramatically ease the tracking drift when the ship is under occlusion.
Furthermore, a forward-backward feedback mechanism is proposed to estimate the scale variation between two consecutive frames.
We prove that these two strategies gain significant improvements over the predator algorithm and also show that the proposed method outperforms several other state-of-the-art trackers.
American Psychological Association (APA)
Xiao, Lei& Xu, Minghai& Hu, Zhongyi. 2018. Real-Time Inland CCTV Ship Tracking. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1205515
Modern Language Association (MLA)
Xiao, Lei…[et al.]. Real-Time Inland CCTV Ship Tracking. Mathematical Problems in Engineering No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1205515
American Medical Association (AMA)
Xiao, Lei& Xu, Minghai& Hu, Zhongyi. Real-Time Inland CCTV Ship Tracking. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1205515
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205515