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Video Surveillance System Using Motion Detection-A Survey


Affiliations
1 Department of Computer Science and Engineering, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal (MS), India
 

Now a days, much of the video surveillance systems require to manually setting a motion detection sensitivity level to generate motion alarms. The performance of motion detection algorithms, embedded in CCTV camera and digital video recorder usually depends upon the preselected motion sensitivity level, which works in all environmental conditions. Due to the preselected sensitivity level, false alarms and detection failures usually exist in video surveillance systems. The proposed motion detection model based upon variational energy provides a robust detection method at various illumination changes and noise levels of image sequences without tuning any parameter manually. We analyze the structure mathematically and demonstrate the effectiveness of the proposed model with numerous experiments in various environmental conditions. Due to the compact structure and efficiency of the proposed model, it could be implemented in a small embedded system.

Keywords

Energy Minimization, Motion Detection, Segmentation, Variational Energy, Video Surveillance.
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  • Video Surveillance System Using Motion Detection-A Survey

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Authors

Radha S. Shirbhate
Department of Computer Science and Engineering, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal (MS), India
Nitish D. Mishra
Department of Computer Science and Engineering, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal (MS), India
Rasika P. Pande
Department of Computer Science and Engineering, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal (MS), India

Abstract


Now a days, much of the video surveillance systems require to manually setting a motion detection sensitivity level to generate motion alarms. The performance of motion detection algorithms, embedded in CCTV camera and digital video recorder usually depends upon the preselected motion sensitivity level, which works in all environmental conditions. Due to the preselected sensitivity level, false alarms and detection failures usually exist in video surveillance systems. The proposed motion detection model based upon variational energy provides a robust detection method at various illumination changes and noise levels of image sequences without tuning any parameter manually. We analyze the structure mathematically and demonstrate the effectiveness of the proposed model with numerous experiments in various environmental conditions. Due to the compact structure and efficiency of the proposed model, it could be implemented in a small embedded system.

Keywords


Energy Minimization, Motion Detection, Segmentation, Variational Energy, Video Surveillance.