BACKGROUND Functional and morphological changes of the heart influence blood flow patterns. Therefore, flow patterns may carry diagnostic and prognostic information. Three-dimensional, time-resolved, three-directional phase contrast cardiovascular magnetic resonance (4D PC-CMR) can image flow patterns with unique detail, and using new flow visualization methods may lead to new insights. The aim...

The data association problem occurs for multiple target tracking applications. Since non-linear and non-Gaussian estimation problems are solved approximately in an optimal way using recursive Monte Carlo methods or particle filters, the association step will be crucial for the overall performance. We introduce a Bayesian data association method based on the particle filter idea and the joint pr...

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...

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of meas...

Hand gesture tracking is one of core method in the field of Human Computer Interaction. In this paper we proposed a tracking method based on Particle Filter framework. Particle Filter algorithm provides a powerful open framework for target tracking and can efficiently deal with motion estimation under the non-linear and nonGaussian environments. The novelty of our method is in the combination o...

A method for Positron Emission Particle Tracking (PEPT) based on optical feature point identification techniques is demonstrated for use in low activity tracking experiments. A population of yeast cells of approximately 125,000 members is activated to roughly 55 Bq/cell by 18F uptake. An in vitro particle tracking experiment is performed with nearly 20 of these cells after decay to 32 Bq/cell. ...