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Enriched Spectral Method for Stiff Convection-Dominated Equations
Hong, Youngjoon,Jung, Chang-Yeol Springer-Verlag 2018 Journal of scientific computing Vol.74 No.3
<P>A novel and simple numerical method for stiff convection-dominated problems is studied in presence of boundary or interior layers. A version of the spectral Chevyshev-collocation method enriched with the so-called corrector functions is investigated. The corrector functions here are designed to capture the stiffness of the layers (see the Appendix), and the proposed method does not rely on the adaptive grid points. The extensive numerical results demonstrate that the enriched spectral methods are very accurate with low computational cost.</P>
Disjoint Particle Filter to Track Multiple Objects in Real-time
( Youngjoon Chai ),( Hyunki Hong ),( Taeyong Kim ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5
Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.