Comparative study of motion detection methods for video surveillance systems

Kamal Sehairi; Fatima Chouireb; Jean Meunier

doi:10.1117/1.JEI.26.2.023025

25 April 2017 Comparative study of motion detection methods for video surveillance systems

Kamal Sehairi, Fatima Chouireb, Jean Meunier

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 2, 023025 (April 2017). https://doi.org/10.1117/1.JEI.26.2.023025

Abstract

The objective of this study is to compare several change detection methods for a monostatic camera and identify the best method for different complex environments and backgrounds in indoor and outdoor scenes. To this end, we used the CDnet video dataset as a benchmark that consists of many challenging problems, ranging from basic simple scenes to complex scenes affected by bad weather and dynamic backgrounds. Twelve change detection methods, ranging from simple temporal differencing to more sophisticated methods, were tested and several performance metrics were used to precisely evaluate the results. Because most of the considered methods have not previously been evaluated on this recent large scale dataset, this work compares these methods to fill a lack in the literature, and thus this evaluation joins as complementary compared with the previous comparative evaluations. Our experimental results show that there is no perfect method for all challenging cases; each method performs well in certain cases and fails in others. However, this study enables the user to identify the most suitable method for his or her needs.

Citation Download Citation

Kamal Sehairi, Fatima Chouireb, and Jean Meunier "Comparative study of motion detection methods for video surveillance systems," Journal of Electronic Imaging 26(2), 023025 (25 April 2017). https://doi.org/10.1117/1.JEI.26.2.023025

Received: 14 December 2016; Accepted: 29 March 2017; Published: 25 April 2017

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