DocumentCode :
2082769
Title :
A study on automatic filter construction for feature extraction with feature reconstruction
Author :
Yano, Yuichiro ; Hashiyama, Tomonori ; Okuma, Shigeru
Author_Institution :
Dept. of Electr. Eng., Nagoya Univ., Japan
Volume :
3
fYear :
2001
fDate :
2001
Firstpage :
1941
Abstract :
Real-time tracking of moving objects in natural scenes has taken a great role in computer vision. In order to track the targets, we have to determine the object models. But, it is hard to determine them in advance. Moreover, to realize real-time operations, each frame operation should be done in short time. In this paper, we propose a filter processing for tracking and an automatic filter construction system. No specific hardware is used. The filters are designed by the system itself in each environment, and are able to extract their color features which are not contained in other areas. The proposed system generates color filters which can derive feature segments using clustering process. After that, it re-assembles the filter to obtain better performance by genetic algorithm. We show how the filters are effective for object detection and tracking a target
Keywords :
computer vision; feature extraction; genetic algorithms; image reconstruction; object detection; target tracking; Intelligent Transport System; automatic filter construction; automatic filter construction system; clustering process; color features extraction; colour filters; computer vision; feature extraction; feature reconstruction; feature segments; filter processing; frame operation; genetic algorithm; moving objects; natural scenes; object detection; object models; real-time operations; real-time tracking; target tracking; targets tracking; Color; Feature extraction; Filters; Genetic algorithms; Hardware; Image reconstruction; Layout; Object detection; Real time systems; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-7108-9
Type :
conf
DOI :
10.1109/IECON.2001.975588
Filename :
975588
Link To Document :
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