A 3D diamond detector for particle tracking

Tracking of Multiple Soccer Players Using a 3d Particle Filter Based on Detector Confidence

In this paper, a novel method for tracking multiple soccer players based on a support vector machine (SVM) and a particle filter is proposed for a monocular fixed soccer video. This paper considers three main topics. First, the state of a particle filter presented in a 3D world coordinate space, instead of a 2D image coordinate space, provides a more realistic model tracking because depth consi...

Particle Tracking in the ATLAS Inner Detector

The Hough transform [1] has recently received much attention as a powerful method of track finding in particle detectors. It has the strength of detecting track segments without having to put in much prior information about the location of the track segments. We present here an alternative algorithm where we show in a specific case how prior information of the tracks can be used to modify the H...

Agnostic Tracking: Nanoscale, High Bandwidth, 3d Particle Tracking for Biology

3d Head Tracking by Particle Filters

In this paper, we propose a particle filter framework for 3D tracking of heads and faces in monocular video sequences. We propose two different approaches. The first approach utilizes a statistical facial texture model as an observation likelihood. The second approach utilizes a deterministic facial texture which is built on-line. The developed approaches have been successfully tested on severa...

A New Modified Particle Filter With Application in Target Tracking

The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...