Multi-view visual surveillance and phantom removal for effective pedestrian detection

Ren, Jie, Xu, Ming, Smith, Jeremy S ORCID: 0000-0002-0212-2365, Zhao, Huimin and Zhang, Rui (2018) Multi-view visual surveillance and phantom removal for effective pedestrian detection. MULTIMEDIA TOOLS AND APPLICATIONS, 77 (14). pp. 18801-18826.

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Official URL: http://dx.doi.org/10.1007/s11042-017-4939-8

Abstract

To increase the robustness of detection in intelligent video surveillance systems, homography has been widely used to fuse foreground regions projected from multiple camera views to a reference view. However, the intersections of non-corresponding foreground regions can cause phantoms. This paper proposes an algorithm based on geometry and colour cues to cope with this problem, in which the homography between different camera views and the Mahalanobis distance between the colour distributions of every two associated foreground regions are considered. The integration of these two matching algorithms improves the robustness of the pedestrian and phantom classification. Experiments on real-world video sequences have shown the robustness of this algorithm.

Item Type:	Article
Uncontrolled Keywords:	Motion detection, Video surveillance, Homography
Depositing User:	Symplectic Admin
Date Deposited:	18 Jul 2017 09:36
Last Modified:	19 Jan 2023 06:59
DOI:	10.1007/s11042-017-4939-8
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3008487