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» Multiple Object Tracking with Kernel Particle Filter
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ICMCS
2005
IEEE
92views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Multi-Kernel Object Tracking
In this paper, we present an object tracking algorithm for the low-frame-rate video in which objects have fast motion. The conventional mean-shift tracking fails in case the reloc...
Fatih Porikli, Oncel Tuzel
ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Robust Tracking-by-Detection using a Detector Confidence Particle Filter
We propose a novel approach for multi-person trackingby- detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
IVC
2007
89views more  IVC 2007»
13 years 7 months ago
Sequential Monte Carlo tracking by fusing multiple cues in video sequences
This paper presents visual cues for object tracking in video sequences using particle filtering. A consistent histogram-based framework is developed for the analysis of colour, e...
Paul Brasnett, Lyudmila Mihaylova, David R. Bull, ...
ICIP
2006
IEEE
14 years 9 months ago
Model-Free, Statistical Detection and Tracking of Moving Objects
A novel statistical approch for detection and tracking of objects is presented here, which uses both edge and color information in a particle filter. The approach does not need an...
Mark Ross
ICMCS
2006
IEEE
167views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Efficient Object Tracking using Control-Based Observer Design
Kernel-based tracking approaches have proven to be more efficient in computation compared to other tracking approaches such as particle filtering. However, existing kernel-based...
Wei Qu, Dan Schonfeld