A recently introduced particle filtering method, called LS-N-IPS, is considered for tracking objects on video sequences. LS-N-IPS is a computationally efficient particle filter that performs better than the standard N-IPS particle filter, when observations are highly peaky, as it is the case of visual object tracking problems with good observation models. An implementation of LS-N-IPS that uses...

Particle filtering is a technique used for filtering non-linear and non-Gaussian dynamical systems. It has found widespread applications in detection, navigation, and tracking problems. Although, in general, particle filtering methods yield improved results, it is difficult to achieve real time performance. This paper presents an improved algorithm to get better convergence. This algorithm uses...

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...

In this paper we investigate object tracking in video sequences by using the potential of particle filtering to process features from video frames. A particle filter (PF) and a Gaussian sum particle filter (GSPF) are developed based upon multiple information cues, namely colour and texture, which are described with highly nonlinear models. The algorithms rely on likelihood factorisation as a pr...

These Video object tracking is an important topic in multimedia technologies. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. In this paper, we proposed a novel approach for video object tracking, named by Density Propagation based Particle Filter (DP-PF). Our approach exploits color histogram to capture the features from object in the video, i...

Novel 3D image analysis and particle matching techniques for the use in the volumetric particle tracking velocimetry have been developed and tested by using synthetic images and experimental images of unsteady 3D flows. A tomography based particle reconstruction scheme along with the subsequent process of individual particle detection and validation was used. The detected particles in the two t...

This paper gives the survey of the existing developments of Visual object target tracking using particle filter from the last decade and discusses the advantage and disadvantages of various particle filters. A variety of different approaches and algorithms have been proposed in literature. At present most of the work in Visual Object Target Tracking is focusing on using particle filter. The par...

A distributed target tracking algorithm based on particle filter is presented to improve the tracking accuracy. By integrating the maximum likelihood estimation algorithm into particle filter model, an optimum weight selection algorithm can be used to reduce overall energy consumption of some sample calculations activities in wireless sensor network. Evaluation results prove that the improved s...

This paper proposes a new technique to build a fully automatic tracking system which handles occlusion problem in a complex environment. In multiple human tracking, handling of occlusion is the challenging issue. When occlusion occurs, kernel based tracking was proven to be the promising approach. Hence, to overcome the occlusion problem the human body was considered to have multiple kernels. I...

13 Milling is a critical process for controlling the properties of the granules produced by roll 14 compaction. In the current study, the positron emission particle tracking (PEPT) technique was 15 used to examine the milling kinematics of roll compacted ribbons at various milling speeds. 16 Microcrystalline cellulose (MCC, Avicel PH-102) was used as the model feed material and a 17 radioactive...