Nonlinear estimation of turbulence and vortical structures has many applications in engineering and in geophysical sciences. In [18] and [41], mathematical foundation of nonlinear filtering methods was developed for viscous flow and for reacting and diffusing systems. The current work is in part an effort to contribute towards concrete computational methods to solve the nonlinear filtering equa...

This paper proposes an integrated framework for fault prediction in the robot dead reckoning system. The integrated framework is built by particle filter and support vector machine (SVM). On the basis, the weighted fault probability parameters can be extracted to train the prediction model. Different from the traditional particle filter fault prediction model, the proposed framework can overcom...

The extended Kalman filter (EKF) has been used as the standard technique for performing recursive nonlinear estimation in vision tracking. In this work, we present an alternative filter with performance superior to that of the EKF. This algorithm, referred to as the Particle filter. Particle filtering was originally developed to track objects in clutter (multi-modal distribution). We present as...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

A novel body pose based human tracking model is proposed for pedestrian tracking. This work investigates the challenges of reliable pedestrian tracking and proposes an improved model under challenging environments. Specifically, it claims that it is useful to exploit the curvature information of different body poses in tracking framework to overcome general tracking problems. In this paper diff...

This paper presents a visual particle filter for tracking a variable number of humans interacting in indoor environments, using multiple cameras. It is built upon a 3-dimensional, descriptive appearance model which features (i) a 3D shape model assembled from simple body part elements and (ii) a fast while still reliable rendering procedure developed on a key view basis of previously acquired b...

In this paper, we propose an efficient and robust multiple target tracking method based on particles filtering and Dezert-Smarandache theory. A model of cue combination is designed with plausible and paradoxical reasoning. The proposed model can resolve the conflict and paradoxes that arise between measured cues due to the partial or total occlusion. Experimental results demonstrate the efficie...