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http://dx.doi.org/10.5391/JKIIS.2009.19.3.311

Real-Time Motion Estimation Algorithm for Mobile Surveillance Robot  

Han, Cheol-Hoon (중앙대학교 전자전기공학부)
Sim, Kwee-Bo (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.3, 2009 , pp. 311-316 More about this Journal
Abstract
This paper presents the motion estimation algorithm on real-time for mobile surveillance robot using particle filter. the particle filter that based on the monte carlo's sampling method, use bayesian conditional probability model which having prior distribution probability and posterior distribution probability. However, the initial probability density was set to define randomly in the most of particle filter. In this paper, we find first the initial probability density using Sum of Absolute Difference(SAD). and we applied it in the partical filter. In result, more robust real-time estimation and tracking system on the randomly moving object was realized in the mobile surveillance robot environments.
Keywords
Object Tracking; Particle Filter; SAD; Bayesian Filter;
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