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» Multiple Object Tracking with Kernel Particle Filter
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CVPR
2005
IEEE
14 years 9 months ago
Using Particles to Track Varying Numbers of Interacting People
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
AVSS
2007
IEEE
14 years 2 months ago
Classifying and tracking multiple persons for proactive surveillance of mass transport systems
We describe a pedestrian classification and tracking system that is able to track and label multiple people in an outdoor environment such as a railway station. The features sele...
Suyu Kong, Conrad Sanderson, Brian C. Lovell
CAIP
2009
Springer
249views Image Analysis» more  CAIP 2009»
14 years 2 months ago
Real-Time Volumetric Reconstruction and Tracking of Hands in a Desktop Environment
A probabilistic framework for vision based volumetric reconstruction and marker free tracking of hand and face volumes is presented, which exclusively relies on off-the-shelf hardw...
Christoph John, Ulrich Schwanecke, Holger Regenbre...
VMV
2001
160views Visualization» more  VMV 2001»
13 years 9 months ago
A Multi-Sensor Object Localization System
This paper presents a localization and tracking system integrating multiple sensors. Object localization results from local sensor systems are fused using a decentralized Kalman f...
Sascha Spors, Rudolf Rabenstein, Norbert Strobel
HYBRID
2003
Springer
14 years 25 days ago
Estimation of Distributed Hybrid Systems Using Particle Filtering Methods
Abstract. Networked embedded systems are composed of a large number of components that interact with the physical world via a set of sensors and actuators, have their own computati...
Xenofon D. Koutsoukos, James Kurien, Feng Zhao