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Stochastic filters have been extensively used for object tracking because of its ability to measure uncertainties and high accuracy. In recent years, the availability of cheap computers with high computational power has led to incorporate tracking systems in many consumer electronics devices such as surveillance cameras and game consoles. In this paper, we compare Kalman filter and particle filter...
Recently, Particle filter has been used for numerous 3D tracking applications especially nonlinear tracking applications which are intractable using Kalman filter or other linear estimator. Particle filter approximates system's dynamics using weighted samples; therefore it can work with variety of systems. In the literature, particle filter is mostly used for articulated body tracking, gesture recognition...
In the recent years, 3D tracking has gained attention due to the perforation of powerful computers and the increasing interest in tracking applications. One of the most common tracking algorithms used is the Kalman filter. Kalman filter is a linear estimator that is based on approximating system's dynamics using Gaussian probability distribution. In this paper, we provide a detailed evaluation of...
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