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http://dx.doi.org/10.5139/JKSAS.2012.40.1.35

Particle Filter Based Feature Points Tracking for Vision Based Navigation System  

Won, Dae-Hee (건국대학교 항공우주정보시스템공학과)
Sung, Sang-Kyung (건국대학교 항공우주정보시스템공학과)
Lee, Young-Jae (건국대학교 항공우주정보시스템공학과)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.40, no.1, 2012 , pp. 35-42 More about this Journal
Abstract
In this study, a feature-points-tracking algorithm is suggested using a particle filter for vision based navigation system. By applying a dynamic model of the feature point, the tracking performance is increased in high dynamic condition, whereas a conventional KLT (Kanade-Lucas-Tomasi) cannot give a solution. Futhermore, the particle filter is introduced to cope with irregular characteristics of vision data. Post-processing of recorded vision data shows that the tracking performance of suggested algorithm is more robust than that of KLT in high dynamic condition.
Keywords
Feature Point Tracking; Particle Filter; KLT; Vision Based Navigation;
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Times Cited By KSCI : 2  (Citation Analysis)
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