scholarly journals Design of Moving Target Detection and Tracking System Based on the Improved Optical Flow Method

2013 ◽  
Author(s):  
Jun Gui ◽  
Tiansi Ma ◽  
Lijun Liu
Keyword(s):  
Optical Flow ◽  
Target Detection ◽  
Tracking System ◽  
Moving Target ◽  
Moving Target Detection ◽  
Flow Method ◽  
Optical Flow Method ◽  
Detection And Tracking

A method of security management of early warning based on mean shift algorithm and data mining

2020 ◽  
Vol 39 (6) ◽  
pp. 8953-8960
Author(s):  
Jin Wang
Keyword(s):  
Optical Flow ◽  
Target Detection ◽  
Early Warning ◽  
Mean Shift ◽  
Security Management ◽  
Moving Target ◽  
Moving Target Detection ◽  
Flow Method ◽  
Optical Flow Method ◽  
And Control

Facing COVID-19 epidemic, many countries have recently strengthened epidemic prevention and control measures. The reliability of safety management is of great significance to personnel management and control during the COVID-19 epidemic period. The focus of security management of early warning is to monitor and identify the moving target. The current optical flow method is vulnerable to the influence of light changes and background movement, and it is not very accurate for moving target detection in dynamic complex background. In this paper, aiming at the traditional Lucas Kanade optical flow method, the inter frame difference method, mean shift clustering algorithm and morphological processing are combined to optimize and improve on the original basis, so that the moving target detection effect in both simple and complex environments is significantly improved. At the same time, the improved algorithm also reduces the execution time to a certain extent, and has a certain resistance to noise interference such as light changes. This has a certain ability test value for personnel control during the epidemic.

The Research of Moving Target Detection and Tracking System Based on DM6437

2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei
Keyword(s):  
Target Detection ◽  
Digital Signal Processor ◽  
Moving Objects ◽  
Tracking System ◽  
Digital Signal ◽  
Gaussian Mixture ◽  
Background Model ◽  
Moving Target ◽  
Moving Target Detection ◽  
Detection And Tracking

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.

Design of moving target detection and tracking system based on cortex-A7 and openCV

2018 ◽  
Vol 35 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Xingli HUANG ◽  
TIANFAN ZHANG ◽  
ZHENGHONG DENG ◽  
ZHE LI
Keyword(s):  
Target Detection ◽  
Tracking System ◽  
Moving Target ◽  
Moving Target Detection ◽  
Detection And Tracking

Study of Multi Target Tracking Algorithm Based on CRF Model

2014 ◽  
Vol 556-562 ◽  
pp. 3860-3863
Author(s):  
Chang Hui Wang
Keyword(s):  
Target Detection ◽  
Video Tracking ◽  
Future Research ◽  
Moving Target ◽  
Complex Scene ◽  
Moving Target Detection ◽  
Optical Flow Method ◽  
Detection And Tracking ◽  
Complex Background ◽  
Multi Target Tracking

Moving target detection and tracking in complex background is the key technology in the field of computer vision, which has become one of the focus researches for many scholars at home and abroad. Many applications, such as robot navigation, video tracking, are closely related with the moving object detection and tracking in complex background. In this paper, we improve the traditional stochastic model and target matching algorithm, combining with the feature optical flow method, to detect and track moving target detection in complex scene, and get online modified CRF model. It provides theoretical support and guidance technology for future research.

scholarly journals Study on the Automatic Basketball Shooting System Based on the Background Subtraction Method

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yan Hu ◽  
Yong Xu
Keyword(s):  
Target Detection ◽  
Background Subtraction ◽  
Detection System ◽  
Moving Target ◽  
Subtraction Method ◽  
Moving Target Detection ◽  
Flow Method ◽  
Optimal Flow ◽  
Optical Flow Method ◽  
Basketball Shooting

There are many drawbacks such as clustering, background updating, inaccurate testing results, and low anti-interference performance in traditional moving target detection theory. In our study, a background subtraction method to automatically capture the basketball shooting trajectory was used to eliminate the drawbacks of the fixed-point shooting system such as cumbersome installation and time and manpower consumption. It also can improve the accuracy and efficiency of moving target detection. We also synthetically compared to common methods including the optical flow method and interframe difference method. Results showed that the background subtraction method has better accuracy with an accuracy rate over about 90% than the interframe subtraction method (88%) and the optimal flow method (85%) and presents excellent robustness with considering variable speed and nonrigid objects. Meanwhile, the automatic detection system for basketball shooting based on background subtraction is built by coupling background subtraction with detection characteristics. The system detection speed built is further accelerated, and the image denoising is improved. The trajectory error rate is about 0.3, 0.4, and 0.5 for the background subtraction method, interframe subtraction method, and optimal flow method, respectively.

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