Recursive Algorithms for Visual Target Tracking Under Colored Measurement Noise
Eli Pale Ramon, Jorge A. Ortega-Contreras, José Amparo Andrade-Lucio, Yuriy S. Shmaliy, Shunyi Zhao · 2020
Visual target tracking is often accompanied with colored measurement noise (CMN) caused by the object and camera frame dynamics, which require special estimation algorithms. In this paper, we consider the Kalman filter (KF) and unbiased finite impulse response (UFIR) filter modified for Gauss-Markov CMN. The algorithms are designed employing measurement differencing and demonstrate a better performance under the CMN then the standard algorithm. Experimental investigations are conducted for several benchmark trajectories, where a target is tracked using a video camera.