Stochastic framework for visual tracking
Ashish Kumar · 2023
Stochastic framework for visual tracking includes probabilistic methods in the Bayesian framework for state estimation. Under the stochastic framework,osition of particles in the current ite linear and Gaussian state estimation is addressed using the Kalman filter, extended Kalman filter, and unscented Kalman filter. In contrast, the nonlinear and non-Gaussian state can be estimated using particle, condensation, and bootstrap filters. In this chapter, we discuss the potential work exploiting the PF filter framework in their appearance model. Also, we experimentally analyze and compare a visual tracking algorithm under the PF framework with existing state-of-the-art in the domain.