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An Object Detection System using Eigen-background and Clustering  

Jeon, Jae-Deok ((주)지노시스템 다차원공간기술연구소)
Lee, Mi-Jeong ((주)BIOSPACE)
Kim, Jong-Ho (인제대학교 전산학과)
Kim, Sang-Kyoon (인제대학교 컴퓨터공학과)
Kang, Byoung-Doo (인제대학교 컴퓨터공학부)
Publication Information
Journal of Korea Multimedia Society / v.13, no.1, 2010 , pp. 47-57 More about this Journal
Abstract
The object detection is essential for identifying objects, location information, and user context-aware in the image. In this paper, we propose a robust object detection system. The System linearly transforms learning data obtained from the background images to Principal components. It organizes the Eigen-background with the selected Principal components which are able to discriminate between foreground and background. The Fuzzy-C-means (FCM) carries out clustering for images with inputs from the Eigen-background information and classifies them into objects and backgrounds. It used various patterns of backgrounds as learning data in order to implement a system applicable even to the changing environments, Our system was able to effectively detect partial movements of a human body, as well as to discriminate between objects and backgrounds removing noises and shadows without anyone frame image for fixed background.
Keywords
Object Detection; Eigen-background; PCA; Clustering; FCM;
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Times Cited By KSCI : 2  (Citation Analysis)
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