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Research on Object Tracking Algorithm Based on SIFT Feature-points Matching

Author: LiMing
Tutor: JiangJianGuoï¼›QiMeiBin
School: Hefei University of Technology
Course: Signal and Information Processing
Keywords: Target detection and tracking Background Update Two scans method SIFT algorithm Feature point matching
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 258
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Abstract


Moving target detection and tracking technology is a hot research topic in the field of computer vision , the real life of a wide range of applications , such as : bank management , medical research , transportation management . SIFT feature point matching - based approach to achieve the target tracking the the SIFT algorithm scale transformation , image scaling and rotation , have good invariance . This article is divided into four chapters , the main contents are as follows : (1) moving target detection part , morphological processing foreground objects integrated into a connected domain background correction , learning rate for the background point ; Object Segmentation section using the two scanning method based on the connected domain , this method can effectively segment the various connected domain . Number of feature points (2 ) the moving target segmentation , SIFT algorithm matching feature points for each goal , write down the number of feature points matching between each goal , determine the match up for the same goal . ( 3) divided the target picture size is much smaller than the size of the original image , therefore , the SIFT algorithm improvements , the Gaussian pyramid down-sampling times, and the difference of Gaussian pyramid layers to adjust , not only to ensure that the same the match between the target feature points still up and false match rate is very small , and shortened the time of the match , time efficiency is improved by the experiments show that the improved algorithm .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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