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Multi Object Tracking Methods Based on Particle Filter and HMM
Abstract – For various application detection of objects movement in a video is an important process. Determination of path of object as time advances is a tedious step. Many proposal for tracking the multiple movement of object has been put forward using various sophisticated techniques. In this paper detail description of the recent object trackers based on particle filtering and Markov Models have been analyzed. The outcome of the analysis is computational efficiency, robustness and computational complexity.
Index Terms – True Positive (TP), False Positive (FP), Markov Chain Monte Carlo (MCMC), Particle Filter (PF), Finite State Machines (FSM), and Hidden Markov Model (HMM).
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL