Comparative Study of Moving Target Analysis System

2014 ◽  
Vol 989-994 ◽  
pp. 3122-3126
Author(s):  
Min Feng ◽  
Huai Chang Du
Keyword(s):  
Object Tracking ◽  
Tracking System ◽  
Moving Target ◽  
Motion Trajectory ◽  
Moving Targets ◽  
Image System ◽  
Target Analysis ◽  
Detection And Tracking ◽  
Analysis System ◽  
Experiment Analysis

This paper compares two kinds of moving target analysis systems, which are the motion history image system and the moving object tracking system. Each system includes two parts which are moving target detection and tracking, achieving respectively detection of the direction of moving targets or representation of motion trajectory. Through experiment analysis of moving human and vehicles, each system is determined which situation it is suitable for.

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.

An Industrial Production Line Dynamic Target Tracking System Based on HAAR and CAMSHIFT

2020 ◽  
Vol 34 (11) ◽  
pp. 2059037
Author(s):  
Xuejun Tian ◽  
Haowen Feng ◽  
Jieyan Chen
Keyword(s):  
Target Tracking ◽  
Tracking System ◽  
Raspberry Pi ◽  
Automation System ◽  
Moving Targets ◽  
Embedded Platform ◽  
System A ◽  
Detection And Tracking ◽  
Camshift Algorithm ◽  
Dynamic Target

Aiming at the detection and tracking of moving targets in industrial automation system, a dynamic target tracking algorithm based on HAAR and CAMSHIFT is proposed. A cascade HAAR classifier is designed and trained for tracking targets. CAMSHIFT algorithm is used to track and detect moving targets quickly. The system is tested on Raspberry Pi embedded platform. The results show that the algorithm can detect the target correctly and track the target effectively.

DEVELOPMENT OF TRACKING SYSTEM FOR MOBILE ROBOT USING IMAGE RECOGNITION ALGORITHMS

2015 ◽  
Vol 39 (3) ◽  
pp. 501-513 ◽  
Author(s):  
Kuo-Lan Su ◽  
Bo-Yi Li ◽  
Kuo-Hsien Hsia
Keyword(s):  
Image Processing ◽  
Control System ◽  
Mobile Robot ◽  
Pid Control ◽  
Balance Control ◽  
Tracking System ◽  
Control Law ◽  
Moving Target ◽  
Image System ◽  
System A

In this paper, an intelligent mobile robot using image processing technology is developed. The mobile robot contains an image system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC-based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The image processing based on OpenCV uses two different tracking methods to track moving targets: MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection). The efficiency of both methods for tracking the moving target on the mobile robot is compared here. The balance control system, with a HOLTEK Semiconductor Company’s HT66F Series 8-bit microprocessor as the processor, uses the PID control law according to the feedback signals of the inclinometer sensor to control the balance level of the loading platform.

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

Optimizing Design of Real-Time Spatial Moving Target Tracking System

2011 ◽  
Vol 328-330 ◽  
pp. 2234-2237
Author(s):  
Dong Sheng Liang ◽  
Zhao Hui Liu ◽  
Wen Liu
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Tracking System ◽  
Processing System ◽  
Video Tracking ◽  
Image Resolution ◽  
Frame Rate ◽  
Moving Target ◽  
Detection And Tracking ◽  
Operation Speed

Achieving the detection and tracking of moving targets has been widely applied in all fields of today's society. Because of the shortcomings of traditional video tracking system, this paper proposes a novel method for designing video processing system based on hardware design of FPGA and DSP, and moving target in video can be detected and tracked by this system. In this system, DSP as the core of the system, it mainly completes the processing algorithms of video and image data, FPGA as a coprocessor, responsible for the completion of the processing of external data and logic. The hardware structure, link configuration, program code and other aspects of system are optimized. Finally, through the experiment, the input frame rate of video is 40frames/s, and the image resolution is 512pixels × 512pixels, median 16bites quantitative image sequence, the system can complete the relevant real-time detection and tracking algorithm and extract targets position of image sequences correctly. The results show that the advantage is that this system has powerful operation speed, real time, high accuracy and stability.

Moving Target Detection and Tracking Based on Improved FCM Algorithm

2020 ◽  
Vol 14 (1) ◽  
pp. 63-74 ◽  
Author(s):  
Wang Ke Feng ◽  
Sheng Xiao Chun
Keyword(s):  
Target Detection ◽  
Clustering Algorithm ◽  
Rapid Development ◽  
Moving Target ◽  
Moving Targets ◽  
Moving Target Detection ◽  
Complex Situation ◽  
Fcm Algorithm ◽  
Detection And Tracking ◽  
Moving Vehicles

With the rapid development of computer intelligence technology, the majority of scholars have a great interest in the detection and tracking of moving targets in the field of video surveillance and have been involved in its research. Moving target detection and tracking has also been widely used in military, industrial control, and intelligent transportation. With the rapid progress of the social economy, the supervision of traffic has become more and more complicated. How to detect the vehicles on the road in real time, monitor the illegal vehicles, and control the illegal vehicles effectively has become a hot issue. In view of the complex situation of moving vehicles in various traffic videos, the authors propose an improved algorithm for effective detection and tracking of moving vehicles, namely improved FCM algorithm. It combines traditional FCM algorithm with genetic algorithm and Kalman filter algorithm to track and detect moving targets. Experiments show that this improved clustering algorithm has certain advantages over other clustering algorithms.

Sign in / Sign up

Export Citation Format

Share Document