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Okamura Kenshiro


A note on moving object detection by principal component analysis

大島商船高等専門学校紀要 Volume 39 Page 65-68
published_at 2006-12
OS10039000010.pdf
[fulltext] 239 KB
Title
主成分分析を用いた物体検出に関する一考察
A note on moving object detection by principal component analysis
Creators Hamamura Hiroyuki
Creators Okamura Kenshiro
Source Identifiers
Creator Keywords
video surveillance systems principal component analysis PCA eigen space
In video surveillance systems, a common method for real-time detection of moving objects involves background subtraction. The background subtraction detects objects by differentiating background pixels from foreground pixels and thresholding the difference. This method contains difficult parts. Because, in real world, the background image varies by gradual and sudden illumination change, moving trees and so on. To handle these problems, we use principal component analysis (PCA) for background images and projection onto eigen space. We analyze the experimental results of real-time operation. Finally, we show the robustness of this method.
Languages jpn
Resource Type departmental bulletin paper
Publishers 大島商船高等専門学校
Date Issued 2006-12
File Version Version of Record
Access Rights open access
Relations
[ISSN]0387-9232
[NCID]AN00031668