Bioinspired Bearing Only Motion Camouflage UAV Guidance for Covert Video Surveillance of a Moving Target

2020 ◽  
pp. 1-4
Author(s):  
Andrey V. Savkin ◽  
Hailong Huang
Keyword(s):  
Video Surveillance ◽  
Moving Target ◽  
Motion Camouflage

The Realization of Moving Target Tracking

2013 ◽  
Vol 389 ◽  
pp. 770-775
Author(s):  
Guang Long Li ◽  
Xiang Bin Zhu ◽  
Hai Geng
Keyword(s):  
Computer Vision ◽  
Target Tracking ◽  
Open Source ◽  
Real Time ◽  
Target Detection ◽  
Video Surveillance ◽  
Target Object ◽  
Moving Target ◽  
Moving Target Tracking ◽  
Detection And Recognition

This paper is mainly talking about processing, analysis and understanding of video signal in intelligent video surveillance, and we designed an efficient target detection and recognition model. Through the model to detect the target object in motion and then track the detected target. Eventually we achieved real-time monitoring of the unguarded areas. The focus of this article is about how to achieve the moving target tracking in OpenCV (Open Source Computer Vision Library) environment.

Moving Objects Detection and Speed Estimation in Intelligent Surveillance System

2013 ◽  
Vol 712-715 ◽  
pp. 2354-2358
Author(s):  
Zhi Hong Xi ◽  
Guang Hui Dong
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Moving Objects ◽  
Operating Conditions ◽  
Background Model ◽  
Moving Target ◽  
Video Surveillance System ◽  
Target Area ◽  
Intelligent Video Surveillance ◽  
Intelligent Video Surveillance System

In order to solve the problem of highway intelligent video surveillance system for effective monitoring of vehicle operating conditions, a fast block background modeling method is proposed in the framework for intelligent video surveillance system. First using statistical histogram to build the background model of the video surveillance system, second using background subtraction method to locate the moving target area, at last using displacement of the minimum exterior rectangle centroid of the moving target between two frames to calculate moving target speed, without the aid calibration. Experimental results show that the proposed method exhibits its superiority in processing time, the time of building background model through 100 frames is 3.8s. The proposed method has good practical value used in intelligent video surveillance.

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