In our method for tracking objects, appearance features are smoothed by robust and adaptive Kalman filters, one to each pixel, making the method robust against occlusions. While t...
A method for object tracking combining the accuracy of mean shift with the robustness to occlusion of Kalman filtering is proposed. At first, an estimation of the object's pos...
Adaptive filtering schemes are subject to different tradeoffs regarding their steady-state misadjustment, speed of convergence and tracking performance. To alleviate these comp...
Particle filtering is an approach to Bayesian estimation of intractable posterior distributions from time series signals distributed by non-Gaussian noise. A couple of variant par...
— In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optim...