A learning approach to fixating on 3D targets with active cameras

Narayan Srinivasa, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fixation of an active camera pair on a given target requires that the pan and tilt angles of the cameras must be set to bring the target to image centers. However, the calibration needed to achieve a specific configuration of real cameras involves tedious estimation of a number of imaging parameters. Fortunately, this excercise is not essential for fixationif images are acquired and used as feedback during the fixation process to continuously direct the cameras to the target. This paper defines a direct mapping from the changes in the direction of target motion in the image plane to changes in camera angles necessary to reduce the disparity between image center and the image plane target location. The mapping captures camera calibration, as well as other effects such as deviations from the assumed imaging model which are difficult to characterize and capture in calibration. The mapping is formulated as a task in nonlinear function approximation and learnt from real data. For computational efficiency, learning is done at multiple resolutions and using a PROBART network. Experimental results are presented using an active vision system.

Original languageEnglish (US)
Title of host publicationComputer Vision - ACCV 1998 - 3rd Asian Conference on Computer Vision, Proceedings
EditorsRoland Chin, Ting-Chuen Pong
PublisherSpringer-Verlag
Pages623-631
Number of pages9
ISBN (Print)3540639306, 9783540639305
DOIs
StatePublished - Jan 1 1997
Event3rd Asian Conference on Computer Vision, ACCV 1998 - Hong Kong, China
Duration: Jan 8 1998Jan 10 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1351
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd Asian Conference on Computer Vision, ACCV 1998
CountryChina
CityHong Kong
Period1/8/981/10/98

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Srinivasa, N., & Ahuja, N. (1997). A learning approach to fixating on 3D targets with active cameras. In R. Chin, & T-C. Pong (Eds.), Computer Vision - ACCV 1998 - 3rd Asian Conference on Computer Vision, Proceedings (pp. 623-631). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1351). Springer-Verlag. https://doi.org/10.1007/3-540-63930-6_175