Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

Joint Authors

Hua-ping, Liu
Xi, Zhenghao
Liu, Heping
Yang, Bin

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-08-17

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm.

First, the multiple object tracking is formulated as an integer programming problem of the flow network.

Then we relax the integer programming to a standard linear programming problem.

Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm.

The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments.

Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

American Psychological Association (APA)

Xi, Zhenghao& Liu, Heping& Hua-ping, Liu& Yang, Bin. 2014. Multiple Object Tracking Using the Shortest Path Faster Association Algorithm. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049775

Modern Language Association (MLA)

Xi, Zhenghao…[et al.]. Multiple Object Tracking Using the Shortest Path Faster Association Algorithm. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1049775

American Medical Association (AMA)

Xi, Zhenghao& Liu, Heping& Hua-ping, Liu& Yang, Bin. Multiple Object Tracking Using the Shortest Path Faster Association Algorithm. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049775

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1049775