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

Civil Engineering

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