Suitability of edge segment based moving object detection for real time video surveillance

Authors:
M. Julius Hossain;M. Ali Akber Dewan;Oksam Chae
Affiliations:
Department of Computer Engineering, Kyung Hee University, Yongin-si, Kyunggi-do, Korea;Department of Computer Engineering, Kyung Hee University, Yongin-si, Kyunggi-do, Korea;Department of Computer Engineering, Kyung Hee University, Yongin-si, Kyunggi-do, Korea
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Year:
2007

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Abstract

This paper investigates the suitability of the proposed edge segment based moving object detection for real time video surveillance. Traditional edge pixel based methods handle each edge pixel individually that is not suitable for robust matching, incorporating knowledge with edges, and tracking it. In the proposed method, extracted edges are represented as segments using an efficiently designed edge class and all the pixels belonging to a segment are processed together. This representation helps us to use the geometric information of edges to speed up detection process and enables incorporating knowledge into edge segments for robust matching and tracking. Experiments with real image sequences and comparisons with some existing methods illustrate the suitability of the proposed approach in moving object detection.