Int. J. of Applied Pattern Recognition   »   2017 Vol.4, No.1

 

 

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Title: Camera movement artefact correction

 

Authors: Joshin John Mathew; Ben Aloysius Gomez

 

Addresses:
Scapeye, Technopark Campus, Trivandrum, India
ARS T & TT, Technopark Campus, Trivandrum, India

 

Abstract: Traffic surveillance systems based on background subtraction model are vulnerable to movements or vibrations in camera posts. Such camera shaking reflects in the form of relative displacements in locations of stationary structures and misinterpreted as valid motion. This artefact is referred to as camera movement artefact. The proposed method extracts the possible regions vulnerable to false motion detection and creates a mask which subtracts out the artefact. The real-time system in which the proposed method is implemented, the allowed processing time per frame is limited to < 30 milliseconds, and the artefact correction mechanism is one of the many components. Hence, this simple mask subtraction provides an optimal solution compared to other per-frame correction mechanisms. Performance is evaluated for multiple test sets and the results show significant reduction in rate of false vehicle detection (36% to 12%) without negotiating available correct vehicle detection (98%).

 

Keywords: background subtraction; camera movement artefact; mask creation; false detection rate; traffic surveillance; camera shaking; false motion detection; false vehicle detection.

 

DOI: 10.1504/IJAPR.2017.10003545

 

Int. J. of Applied Pattern Recognition, 2017 Vol.4, No.1, pp.14 - 26

 

Submission date: 08 May 2016
Date of acceptance: 12 May 2016
Available online: 01 Mar 2017

 

 

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