Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Computer Knowledge and Technology》 2018-24
Add to Favorite Get Latest Update

A summary of Moving Target Detection and Tracking Algorithm

WANG Hui;Anhui Sanlian University;  
Moving target detection and tracking are widely used in multimedia images, video surveillance,etc. Over the years, peoplehave done a lot of in-depth research in this field, and published a lot of significant results. However, target occlusion, scale changeand illumination change still have a great impact on tracking results. To solve these problems, researchers are still studying how toconstruct a robust tracking algorithm. In this paper, we briefly describe the development of common algorithms for moving objectdetection and tracking in recent years. The principle of frame difference method, background subtraction and optical flow methodfor moving object detection is simply analyzed. The Meanshift algorithm, Kalman filter and particle filter method for moving targettracking are described. In the end, a brief introduction to the theory of compressed sensing is made. And two algorithms based onthis theory are described: sparse representation tracking and compressive tracking.
【Fund】: 安徽三联学院校级科研基金自然科学重点项目:中医经络按摩机器人视觉系统研究(KJZD2017009)
【CateGory Index】: TP391.41
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved