Active-camera calibration using iterative image feature localization

W. Brent Seales, David Eggert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This work presents a new approach to the problem of calibrating a zooming camera using staged global optimization. The input is a sequence of images of a known calibration target obtained at different mechanical zoom settings. We avoid heavy dependence on individual, strongly localized features. Feature localization is obtained iteratively, formulated as part of the error criterion used in various passes of the optimization process. The staged optimization process considers all images simultaneously, representing the parameters of the final calibrated camera as a function of zoom. Our experiments on synthetic images and real stereo image sequences (from a zooming stereo rig) achieve epipolar correspondences at all zoom settings to an accuracy of 1 pixel.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 6th International Conference, CAIP 1995, Proceedings
EditorsVaclav Hlavac, Radim Sara
Number of pages6
StatePublished - 1995
Event6th International Conference on Computer Analysis of Images and Patterns, CAIP 1995 - Prague, Czech Republic
Duration: Sep 6 1995Sep 8 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Conference on Computer Analysis of Images and Patterns, CAIP 1995
Country/TerritoryCzech Republic

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1995.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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