Application of Integral Optical Flow for Determining Crowd Movement from Video Images Obtained Using Video Surveillance Systems

2018 ◽  
Vol 85 (1) ◽  
pp. 126-133 ◽  
Author(s):  
H. Chen ◽  
Sh. Ye ◽  
O. V. Nedzvedz ◽  
S. V. Ablameyko
2019 ◽  
Vol 43 (4) ◽  
pp. 647-652 ◽  
Author(s):  
H. Chen ◽  
S. Ye ◽  
A. Nedzvedz ◽  
O. Nedzvedz ◽  
H. Lv ◽  
...  

Road traffic analysis is an important task in many applications and it can be used in video surveillance systems to prevent many undesirable events. In this paper, we propose a new method based on integral optical flow to analyze cars movement in video and detect flow extreme situations in real-world videos. Firstly, integral optical flow is calculated for video sequences based on optical flow, thus random background motion is eliminated; secondly, pixel-level motion maps which describe cars movement from different perspectives are created based on integral optical flow; thirdly, region-level indicators are defined and calculated; finally, threshold segmentation is used to identify different cars movements. We also define and calculate several parameters of moving car flow including direction, speed, density, and intensity without detecting and counting cars. Experimental results show that our method can identify cars directional movement, cars divergence and cars accumulation effectively.


Informatica ◽  
2018 ◽  
Vol 29 (2) ◽  
pp. 211-232 ◽  
Author(s):  
Huafeng Chen ◽  
Olga Nedzvedz ◽  
Shiping Ye ◽  
Sergey Ablameyko

Author(s):  
A A Morozov ◽  
O S Sushkova ◽  
I A Kershner ◽  
A F Polupanov

The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be used under the control of a specially trained operator. As a result, the terahertz video surveillance appears to be more expensive and less efficient in comparison with the standard approach based on the organizing security perimeters and manual inspection of the visitors. In the paper, the problem of the development of a method of automatic analysis of the terahertz video images is considered. As a basis for this method, it is proposed to use the semantic fusion of video images obtained using different physical principles, the idea of which is in that the semantic content of one video image is used to control the processing and analysis of another video image. For example, the information about 3D coordinates of the body, arms, and legs of a person can be used for analysis and proper interpretation of color areas observed on a terahertz video image. Special means of the object-oriented logic programming are developed for the implementation of the semantic fusion of the video data, including special built-in classes of the Actor Prolog logic language for acquisition, processing, and analysis of video data in the visible, infrared, and terahertz ranges as well as 3D video data.


Author(s):  
D. Nethaji ◽  
Mary Joans ◽  
Mrs. S. J. Grace Shoba

Video surveillance has been a popular security tool for years. Video surveillance systems produce huge amounts of data for storage and display. Long-term human monitoring of the acquired video is impractical and in-effective. This paper presents a novel solution for real-time cases that identify and record only “interesting” video frames containing motion. In addition to traditional methods for compressing individual video images, we could identify and record only “interesting” video images, such as those images with significant amounts of motion in the field of view. The model would be built in simulink, one of tools in matlab and incorporated with davinci code processor, a video processor. That could significantly help reduce the data rates for surveillance-specific applications.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.


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