Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Differential Evolution and Condensation Algorithms for License Plate Tracking
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
ACM Computing Surveys (CSUR)
Rao-Blackwellized particle filter for multiple target tracking
Information Fusion
Computer Vision and Image Understanding
Tracking moving optima using kalman-based predictions
Evolutionary Computation
Model based human motion tracking using probability evolutionary algorithm
Pattern Recognition Letters
Tracking the soccer ball using multiple fixed cameras
Computer Vision and Image Understanding
An Automatic Moving Object Detection Algorithm for Video Surveillance Applications
ICESS '09 Proceedings of the 2009 International Conference on Embedded Software and Systems
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
Studies on intrinsic summary evaluation
International Journal of Artificial Intelligence and Soft Computing
Multiple and variable target visual tracking for video-surveillance applications
Pattern Recognition Letters
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Real-Time Modeling of 3-D Soccer Ball Trajectories From Multiple Fixed Cameras
IEEE Transactions on Circuits and Systems for Video Technology
Motion detection with pyramid structure of background model for intelligent surveillance systems
Engineering Applications of Artificial Intelligence
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Real time video surveillance is an interdisciplinary task that has perceived reasonable attention safety and security purpose. Such video surveillance task is challenging task which involves detection of one or more moving objects from a video sequence. Though there has been several analysis made on different perspectives of video surveillance, there are many issues left open for investigation namely segmentation of moving objects, foreground and background detection, preprocessing, feature extraction and so on. This paper presents some in depth study on the challenges and issues in many real time video surveillance applications, highlighting the need for an improved video tracking algorithms for effective design of video surveillance systems. In addition the paper focuses on to provide a new proposal in three fold ways, there by producing a refined approach as compared to previous techniques for real time video surveillance. The proposed system is experimented over the synthetic data set and also tested under commercial data repository, which leads to results that were promising.