scholarly journals Using Sensor Network in Motion Detection Based on Deep Full Convolutional Network Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Qichang Xu
Keyword(s):  
Sensor Network ◽  
Target Detection ◽  
Network Model ◽  
Motion Detection ◽  
Video Frame ◽  
Detection Accuracy ◽  
Moving Target ◽  
Moving Target Detection ◽  
Convolutional Network ◽  
Video Scene

Aiming at the shortcomings of traditional moving target detection methods in complex scenes such as low detection accuracy and high complexity, and not considering the overall structure information of the video frame image, this paper proposes a moving-target detection based on sensor network. First, a low-power motion detection wireless sensor network node is designed to obtain motion detection information in real time. Secondly, the background of the video scene is quickly extracted by the time domain averaging method, and the video sequence and the background image are channel-merged to construct a deep full convolutional network model. Finally, the network model is used to learn the deep features of the video scene and output the pixel-level classification results to achieve moving target detection. This method not only can adapt to complex video scenes of different sizes but also has a simple background extraction method, which effectively improves the detection speed.

scholarly journals Detection and Adaptive Video Processing of Hyperopia Scene in Sports Video

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qingjie Chen ◽  
Minkai Dong
Keyword(s):  
Real Time ◽  
Target Detection ◽  
Motion Detection ◽  
Difference Method ◽  
Detection Algorithm ◽  
Moving Target ◽  
Target Area ◽  
Moving Target Detection ◽  
Target Extraction ◽  
Motion Video

In the research of motion video, the existing target detection methods are susceptible to changes in the motion video scene and cannot accurately detect the motion state of the target. Moving target detection technology is an important branch of computer vision technology. Its function is to implement real-time monitoring, real-time video capture, and detection of objects in the target area and store information that users are interested in as an important basis for exercise. This article focuses on how to efficiently perform motion detection on real-time video. By introducing the mathematical model of image processing, the traditional motion detection algorithm is improved and the improved motion detection algorithm is implemented in the system. This article combines the advantages of the widely used frame difference method, target detection algorithm, and background difference method and introduces the moving object detection method combining these two algorithms. When using Gaussian mixture model for modeling, improve the parts with differences, and keep the unmatched Gaussian distribution so that the modeling effect is similar to the actual background; the binary image is obtained through the difference between frames and the threshold, and the motion change domain is extracted through mathematical morphological filtering, and finally, the moving target is detected. The experiment proved the following: when there are more motion states, the recall rate is slightly better than that of the VIBE algorithm. It decreased about 0.05 or so, but the relative accuracy rate increased by about 0.12, and the increase ratio is significantly higher than the decrease ratio. Departments need to adopt effective target extraction methods. In order to improve the accuracy of moving target detection, this paper studies the method of background model establishment and target extraction and proposes its own improvement.

Applying the Technology of Moving Target Detection in Missile Training Equipment

2017 ◽  
Vol 31 (06) ◽  
pp. 1750017 ◽  
Author(s):  
Guoqing Zhou ◽  
Xinghui Wang ◽  
Xinrong Li
Keyword(s):  
Target Detection ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Video Frame ◽  
Moving Target ◽  
Moving Target Detection ◽  
Mapping Algorithm ◽  
Frame Difference ◽  
Detection Technology ◽  
System Maintenance

The process of missile launch training was confined to the virtual scene in the past. So, cooperating with an artillery college, the group makes the moving target detection technology to be applied in missile training equipment, so as to make the training apply to the field operations. This paper presents the frame difference mapping algorithm, which is used to detect the moving target in the background of moving video frame. According to the target region which is given out by the system in the graphical interface, the students do the launching missile training. The moving target detection algorithm which is provided with the low complexity and the high accuracy, i.e. proposed by the paper, is based on Gauss mixture model and frame difference mapping. The mechanism of layered-graphics and the message agent which makes the modules in the system be independent of each other are used in the system designing. So, the module coupling degree in terms of this mechanism is lower than before. This mechanism brings convenience to system maintenance and upgrade, especially for the system’s transplanting to the real missile launch system in future.

Multi-channel SAR Ground Moving Target Detection Based on Multistage Wiener Filter

2011 ◽  
Vol 33 (10) ◽  
pp. 2420-2426
Author(s):  
Bin Tian ◽  
Dai-yin Zhu ◽  
Di Wu ◽  
Zhao-da Zhu
Keyword(s):  
Target Detection ◽  
Wiener Filter ◽  
Moving Target ◽  
Moving Target Detection ◽  
Multistage Wiener Filter ◽  
Ground Moving Target Detection

A NEW APPROACH FOR MOVING TARGET DETECTION USING BARTLETT METHOD FOR SPECTRAL ESTIMATION

2011 ◽  
Vol 11 (ASAT CONFERENCE) ◽  
pp. 1-15
Author(s):  
Abdel Rahman Elbardawiny ◽  
Khairy Elbarbary ◽  
Fathy Ahmed
Keyword(s):  
Target Detection ◽  
Spectral Estimation ◽  
Moving Target ◽  
Moving Target Detection ◽  
New Approach
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