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» Multiple Object Tracking with Kernel Particle Filter
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CVPR
2005
IEEE
16 years 4 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
95
Voted
AVSS
2007
IEEE
15 years 8 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»
15 years 9 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»
15 years 3 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
15 years 7 months 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