Particle Tracking Velocimetry by Means of Particle Swarm Optimization

Particle Filter versus Particle Swarm Optimization for Object Tracking

Recently, Particle Swarm Optimization (PSO) is introduced as an alternative to Particle Filter (PF) for object tracking. In this work, we compare a PSO tracker with two PF trackers, a classical PF tracker and an Enhanced Particle Filter (EPF) tracker, introduced in this paper. The accuracy of the tracking and, in particular, occlusion handling are considered. The different trackers are implemen...

Multiple Object Tracking using Particle Swarm Optimization

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multi...

Visual Tracking using Particle Swarm Optimization

The problem of robust extraction of visual odometry from a sequence of images obtained by an eye in hand camera configuration is addressed. A novel approach toward solving planar template based tracking is proposed which performs a non-linear image alignment for successful retrieval of camera transformations. In order to obtain global optimum a bio-metaheuristic is used for optimization of simi...

Particle Swarm Optimization Based Object Tracking

This paper proposes a particle swarm optimization based algorithm for object tracking in image sequences. In each frame the particles are drawn from a Gaussian distribution in order to cover the promising object locations and afterwards the particle swarm optimization takes place in order to concentrate the particles near the true object state. The aim of the particle swarm optimization is to s...

Particle Image Velocimetry by Feature Tracking