Object Motion Detection Methods for Real-Time Video Surveillance: A Survey with Empirical Evaluation

2019 ◽  
pp. 663-679
Author(s):  
Surender Singh ◽  
Ajay Prasad ◽  
Kingshuk Srivastava ◽  
Suman Bhattacharya
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Motion Detection ◽  
Empirical Evaluation ◽  
Object Motion ◽  
Detection Methods

scholarly journals Comparative study of motion detection methods for video surveillance systems

2017 ◽  
Vol 26 (2) ◽  
pp. 023025 ◽  
Author(s):  
Kamal Sehairi ◽  
Fatima Chouireb ◽  
Jean Meunier
Keyword(s):  
Comparative Study ◽  
Video Surveillance ◽  
Motion Detection ◽  
Detection Methods ◽  
Surveillance Systems

Design of Video Motion Detect System Based on SOPC

2012 ◽  
Vol 241-244 ◽  
pp. 2263-2267
Author(s):  
Jiang Chun Xu ◽  
Shi Bo Hao ◽  
Xi Liu
Keyword(s):  
System Design ◽  
Real Time ◽  
Video Surveillance ◽  
Motion Detection ◽  
Processing Speed ◽  
Video Data ◽  
Experimental Results ◽  
Design Scheme ◽  
System A

It is very necessary to apply motion detection to video surveillance in order to enhance the performance of system. A new design scheme of video motion detect system based on System On a Programmable Chip is proposed. Two cameras will capture the video data in real-time, and transmitted to DE2_70 development board. After the system which is on a programmable chip based on FPGA processing, the cameras survey whether an illegal personnel is in the range of cameras. The system achieves that two-way video to switch through the switch button. The experimental results show that the SOPC realization of the system design improves the processing speed, and the system also has good flexibility.

scholarly journals FPGA-Based Real-Time Motion Detection for Automated Video Surveillance Systems

Electronics ◽  
2016 ◽  
Vol 5 (4) ◽  
pp. 10 ◽  
Author(s):  
Sanjay Singh ◽  
Chandra Shekhar ◽  
Anil Vohra
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Motion Detection ◽  
Surveillance Systems ◽  
Time Motion ◽  
Automated Video Surveillance

scholarly journals Threshold Modeling of Basic Statistical Methods for Effective Motion Detection in Video Surveillance

2021 ◽  
Vol 12 (2) ◽  
pp. 569-575
Author(s):  
Surender Singh, Et. al.
Keyword(s):  
Statistical Methods ◽  
Video Surveillance ◽  
Motion Detection ◽  
Object Motion ◽  
Data Sets ◽  
Refresh Rate ◽  
Quality Of Motion ◽  
Future Experimentation ◽  
Parameter Values

This paper empirical investigates two basic statistical methods namely Adaptive Median and Adaptive Mean for motion detection in video surveillance for the optimization of parameters namely threshold and the refresh rate of background frame used in these methods. Experimentation shows that the optimum choice of parameters majorly affects the quality of motion detection. The performance of methods for different parameters is measured using precision, recall  and f1-score. PR curves are also drawn which are based on precision and recall values to show the effect of different parameters. Test data includes six data sets from different scenarios of ‘CDNet2012’. Experimental results verify that for every method there are fixed values of parameters with slight variations which gives better result of object motion. These parameter values can be used or adapted for future experimentation on these methods with respect to each scenario.

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