Particle-tracking methods are widely used in fluid mechanics and multi-target tracking research because of their unique ability to reconstruct long trajectories with high spatial and temporal resolution. Researchers have recently demonstrated 3D tracking of several objects in real time, but as the number of objects is increased, real-time tracking becomes impossible due to data transfer and pro...

Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutiona...

Abstract The phenomenon of weakness will – not doing what we perceive as the best action is recognized by neoclassical economics due to axiomatic assumptions revealed preference theory (RPT) that people do for them. However, present bias shows have different preferences over time. As they cannot be compared utility measurements, economists need normatively decide between selves (short- versus l...

A particle tracking code is developed to solve a general time-fractional diffusion equation (FDE), yielding a Lagrangian framework that can track particle dynamics. Extensive simulations demonstrate the efficiency and flexibility of this simple Langevin approach. Many real problems require a vector FDE with variable parameters and multiscaling spreading rates. For these problems, particle track...

hand gesture recognition is very important to communicate in sign language. in this paper, an effective object tracking and hand gesture recognition method is proposed. this method is combination of two well-known approaches, the mean shift and the motion detection algorithm. the mean shift algorithm can track objects based on the color, then when hand passes the face occlusion happens. several...

Pedestrian tracking is a critical problem in the field of computer vision. Particle filters have been proven to be very useful in pedestrian tracking for nonlinear and non-Gaussian estimation problems. However, pedestrian tracking in complex environment is still facing many problems due to changes of pedestrian postures and scale, moving background, mutual occlusion, and presence of pedestrian....

This paper proposes the use of a particle filter with embedded particle swarm optimization as an efficient and effective way of dealing with 3d model-based human body tracking. A particle swarm optimization algorithm is utilized in the particle filter to shift the particles toward more promising configurations of the human model. The algorithm is shown to be able of tracking full articulated bo...