Recursive Camera Autocalibration with the Kalman Filter

Gallego Bonet, Guillermo and Ronda Prieto, José Ignacio and Valdés Morales, Antonio and García Santos, Narciso (2007). Recursive Camera Autocalibration with the Kalman Filter. In: "IEEE International Conference on Image Processing (ICIP)", 16-19 Sept 2007, San Antonio, USA.

Description

Title: Recursive Camera Autocalibration with the Kalman Filter
Author/s:
  • Gallego Bonet, Guillermo
  • Ronda Prieto, José Ignacio
  • Valdés Morales, Antonio
  • García Santos, Narciso
Item Type: Presentation at Congress or Conference (Poster)
Event Title: IEEE International Conference on Image Processing (ICIP)
Event Dates: 16-19 Sept 2007
Event Location: San Antonio, USA
Title of Book: IEEE International Conference on Image Processing (ICIP)
Date: September 2007
Subjects:
Freetext Keywords: Camera autocalibration, Euclidean upgrading, Three-dimensional reconstruction, Algebraic geometry, Space lines, Square pixels, Known Pixel Shape, Absolute Quadratic Complex, Absolute Line Quadric, Kalman Filter, Recursive
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
UPM's Research Group: http://www.gti.ssr.upm.es/~jir/comp_vis/index.html
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Given a projective reconstruction of a 3D scene, we address the problem of recovering the Euclidean structure of the scene in a recursive way. This leads to the application of Kalman filtering to the problem of camera autocalibration and to new algorithms for the autocalibration of cameras with varying parameters. This has benefits in saving memory and computational effort, and obtaining faster updates of the 3D Euclidean structure of the scene under consideration.

More information

Item ID: 10421
DC Identifier: http://oa.upm.es/10421/
OAI Identifier: oai:oa.upm.es:10421
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4379802
Deposited by: Dr Guillermo Gallego Bonet
Deposited on: 02 Mar 2012 09:05
Last Modified: 20 Apr 2016 18:38
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