Real-time background subtraction for video surveillance: From research to reality

2010 ◽  
Author(s):  
M Hedayati ◽  
W M D W Zaki ◽  
A Hussain
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Background Subtraction

Real-time background subtraction-based video surveillance of people by integrating local texture patterns

2013 ◽  
Vol 8 (4) ◽  
pp. 665-676 ◽  
Author(s):  
Hefeng Wu ◽  
Ning Liu ◽  
Xiaonan Luo ◽  
Jiawei Su ◽  
Liangshi Chen
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Local Texture

Critical Video Surveillance and Identification of Human Behavior Analysis of ATM Security Systems

2016 ◽  
pp. 93-118
Author(s):  
M. Sivabalakrishnan ◽  
R. Menaka ◽  
S. Jeeva
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Surveillance System ◽  
Security Systems ◽  
Research Issues ◽  
Background Estimation ◽  
Security Officers ◽  
Abnormal Behaviors ◽  
Human Behavior Analysis

Video surveillance cameras are placed in many places such as bank, hospital, toll gates, airports, etc. To take advantage of the video in real time, a human must monitor the system continuously in order to alert security officers if there is an emergency. Besides, for event detection a person can observe four cameras with good accuracy at a time. Therefore, this requires expensive human resources for real time video surveillance using current technology. The trajectory of one or more targets obtains for object tracking while recording above space and time. By tracking various objects, the burden of detection by human sentinels is greatly alleviated. Efficient and reliable automatic alarm system is useful for many ATM surveillance applications. ATM Video monitoring systems present many challenging research issues in human abnormal behaviors detection approaches. The framework of ATM video surveillance system encompassing various factors, such as image acquisition, background estimation, background subtraction, segmentation, people counting and tracking are briefly discussed in this chapter.

Critical Video Surveillance and Identification of Human Behavior Analysis of ATM Security Systems

2019 ◽  
pp. 315-341
Author(s):  
M. Sivabalakrishnan ◽  
R. Menaka ◽  
S. Jeeva
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Surveillance System ◽  
Security Systems ◽  
Research Issues ◽  
Background Estimation ◽  
Security Officers ◽  
Abnormal Behaviors ◽  
Human Behavior Analysis

Video surveillance cameras are placed in many places such as bank, hospital, toll gates, airports, etc. To take advantage of the video in real time, a human must monitor the system continuously in order to alert security officers if there is an emergency. Besides, for event detection a person can observe four cameras with good accuracy at a time. Therefore, this requires expensive human resources for real time video surveillance using current technology. The trajectory of one or more targets obtains for object tracking while recording above space and time. By tracking various objects, the burden of detection by human sentinels is greatly alleviated. Efficient and reliable automatic alarm system is useful for many ATM surveillance applications. ATM Video monitoring systems present many challenging research issues in human abnormal behaviors detection approaches. The framework of ATM video surveillance system encompassing various factors, such as image acquisition, background estimation, background subtraction, segmentation, people counting and tracking are briefly discussed in this chapter.

Smart Video Surveillance Systems and Identification of Human Behavior Analysis

2019 ◽  
pp. 64-97
Author(s):  
M. Sivabalakrishnan ◽  
R. Menaka ◽  
S. Jeeva
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Background Subtraction ◽  
Surveillance System ◽  
Surveillance Systems ◽  
Cloud Environment ◽  
Background Estimation ◽  
Security Officers ◽  
Smart Surveillance ◽  
Human Behavior Analysis

Smart surveillance cameras are placed in many places such as bank, hospital, toll gates, airports, etc. To take advantage of the video in real time, a human must monitor the system continuously in order to alert security officers if there is an emergency. Besides, for event detection a person can observe four cameras with good accuracy at a time. Therefore, this requires expensive human resources for real-time video surveillance using current technology. The framework of ATM video surveillance system encompassing various factors, such as image acquisition, background estimation, background subtraction, store, and further process like segmentation, people counting, and tracking are done in cloud environment briefly discussed in this chapter.

Safety Monitoring and Warning System for Subway Construction Workers using Wearable Technology

2019 ◽  
Vol 13 ◽  
Author(s):  
Jun-hua Chen ◽  
Da-hu Wang ◽  
Cun-yuan Sun
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Early Warning ◽  
Warning System ◽  
Safety Monitoring ◽  
Wearable Technology ◽  
Construction Workers ◽  
Great Success ◽  
Subway Construction ◽  
Monitoring And Early Warning

Objective: This study focused on the application of wearable technology in the safety monitoring and early warning for subway construction workers. Methods: With the help of real-time video surveillance and RFID positioning which was applied in the construction has realized the real-time monitoring and early warning of on-site construction to a certain extent, but there are still some problems. Real-time video surveillance technology relies on monitoring equipment, while the location of the equipment is fixed, so it is difficult to meet the full coverage of the construction site. However, wearable technologies can solve this problem, they have outstanding performance in collecting workers’ information, especially physiological state data and positioning data. Meanwhile, wearable technology has no impact on work and is not subject to the inference of dynamic environment. Results and conclusion: The first time the system applied to subway construction was a great success. During the construction of the station, the number of occurrences of safety warnings was 43 times, but the number of occurrences of safety accidents was 0, which showed that the safety monitoring and early warning system played a significant role and worked out perfectly.

Accelerating real‐time object detection in high‐resolution video surveillance

2021 ◽  
Author(s):  
Yuefeng Wang ◽  
Kuang Mao ◽  
Tong Chen ◽  
Yanglong Yin ◽  
Shuibing He ◽  
...  
Keyword(s):  
High Resolution ◽  
Object Detection ◽  
Real Time ◽  
Video Surveillance

scholarly journals Remote Video Surveillance System Based on Direct Show and Image Compression

2013 ◽  
Vol 756-759 ◽  
pp. 439-442
Author(s):  
Shang Fu Gong ◽  
Li Gang Wu ◽  
Yan Jun Wang
Keyword(s):  
Image Compression ◽  
Real Time ◽  
Video Surveillance ◽  
Data Transmission ◽  
Video Transmission ◽  
Massive Data ◽  
Time Requirements ◽  
Rich Information ◽  
Precautionary Measures ◽  
Application Requirements

Video surveillance, convenience and rich information, has been widely used in security, protection, monitoring and other occasions, and has already been one of the most important precautionary measures in commercial, residential and transportation areas. However, considering the massive data transmission needs and higher real-time requirements for video surveillance, a remote video surveillance plan has been put forward on the analysis basis of Microsoft DirectShow and Image Compression. This plan adopts the C/S structure, adapts to the requirements of real-time video transmission, with a better fluency. In addition, the picture clarity satisfies the application requirements.

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