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In this paper, a robust visual tracking method is proposed to track an object in dynamic conditions that include motion blur, illumination changes, pose variations, and occlusions. To cope with these challenges, multiple trackers with different feature descriptors are utilized, and each of which shows different level of robustness to certain changes in an(More)
In this paper we present a general solution for multi-target tracking with superpositional measurements. Measurements that are functions of the sum of the contributions of the targets present in the surveillance area are called superpositional measurements. We base our modelling on Labeled Random Finite Set (RFS) in order to jointly estimate the number of(More)
In this paper, we propose an efficient and accurate visual tracker equipped with a new particle filtering algorithm and robust subspace learning-based appearance model. The proposed visual tracker avoids drifting problems caused by abrupt motion changes and severe appearance variations that are well-known difficulties in visual tracking. The proposed(More)
This paper is concerned with distributed extended Kalman filtering (DEKF) for simultaneous pedestrian and multiple mobile robots localization. Here, extended Kalman filter (EKF) is applied to the multiple robots for the pedestrian localization. The estimate from each robot is fused by distributed algorithm to improve the accuracy. Furthermore, we used(More)
A receding horizon filtering problem for nonlinear continuous-time stochastic systems is considered. The paper presents the optimal receding horizon filtering equations. Derivation of the equations is based on the Kushner-Stratonovich and Fokker-Planck-Kolmogorov equations for conditional and unconditional density functions. This result could be a(More)
In this correspondence, a new multi-target tracking (MTT) algorithm based on the probability hypothesis density (PHD) filtering framework is designed in order to improve tracking performance via the proposal of two contributions. First, unlike typical existing systems, Doppler information is additionally employed to enhance the clutter rejection capability.(More)
In this paper, we propose a new method for 3D people tracking with RGB-D observations. The proposed method fuses RGB and depth data via a switching observation model. Specifically, the proposed switching observation model intelligently exploits both final detection results and raw signal intensity in a complementary manner in order to cope with missing(More)