Development of swift motion tracking via intensively adaptive Markov-Chain Monto Carlo sampling

Abstract

In computer vision robust motion tracking became challenging task due to its uncertainty. Conventional method proposed for motion tracking suffer from well-known local trap problem & poor convergence rate.so we propose novel sampling based tracking for motion in Bayesian filtering. Adaptive estimation of filtering distribution is estimated when sampling… (More)

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@article{Subramaniyan2014DevelopmentOS, title={Development of swift motion tracking via intensively adaptive Markov-Chain Monto Carlo sampling}, author={Rajeswari Subramaniyan and M. Senthil Kumar and M. Ponmala and S. Devi Mahalakshmi}, journal={2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies}, year={2014}, pages={1361-1364} }