Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling

Mohedano del Pozo, Raúl and García Santos, Narciso (2011). Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling. In: "18th IEEE International Conference on Image Processing, ICIP 2011", 11/09/2011 - 14/09/2011, Bruselas, Belgica. ISBN 978-1-4577-1304-0.

Description

Title: Simultaneous 3D object tracking and camera parameter estimation by Bayesian methods and transdimensional MCMC sampling
Author/s:
  • Mohedano del Pozo, Raúl
  • García Santos, Narciso
Item Type: Presentation at Congress or Conference (Article)
Event Title: 18th IEEE International Conference on Image Processing, ICIP 2011
Event Dates: 11/09/2011 - 14/09/2011
Event Location: Bruselas, Belgica
Title of Book: Proceedings of 18th IEEE International Conference on Image Processing, ICIP 2011
Date: 2011
ISBN: 978-1-4577-1304-0
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Multi-camera 3D tracking systems with overlapping cameras represent a powerful mean for scene analysis, as they potentially allow greater robustness than monocular systems and provide useful 3D information about object location and movement. However, their performance relies on accurately calibrated camera networks, which is not a realistic assumption in real surveillance environments. Here, we introduce a multi-camera system for tracking the 3D position of a varying number of objects and simultaneously refin-ing the calibration of the network of overlapping cameras. Therefore, we introduce a Bayesian framework that combines Particle Filtering for tracking with recursive Bayesian estimation methods by means of adapted transdimensional MCMC sampling. Addi-tionally, the system has been designed to work on simple motion detection masks, making it suitable for camera networks with low transmission capabilities. Tests show that our approach allows a successful performance even when starting from clearly inaccurate camera calibrations, which would ruin conventional approaches.

More information

Item ID: 12211
DC Identifier: http://oa.upm.es/12211/
OAI Identifier: oai:oa.upm.es:12211
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6115833
Deposited by: Memoria Investigacion
Deposited on: 29 Aug 2012 08:24
Last Modified: 21 Apr 2016 11:25
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