Using Projective Vision to find Camera Positions in an Image Sequence

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ConferenceIn Vision Interface 2000, May 2000., Montréal, Québec, Canada
Subjectprojective vision; motion problems; structure from motion; camera positions; model building; problèmes de mouvement; structuration d'après le mouvement; positions de caméra; construction de modèle
AbstractThe paradigm of projective vision has recently become popular. In this paper we describe a system for computing camera positions from an image sequence using projective methods. Projective methods are normally used to deal with uncalibrated images. However, we claim that even when calibration information is available it is often better to use the projective approach. By computing the trilinear tensor it is possible to produce a reliable and accurate set of correspondences. When calibration information is available these correspondences can be sent directly to a photogrammetric program to produce a set of camera positions. We show one way of dealing with the problem of cumulative error in the tensor computation and demonstrate that projective methods can handle surprisingly large baselines, in certain cases one third of the image size. In practice projective methods, along with random sampling algorithms, solve the correspondence problem for many image sequences. To aid in the understanding of this relatively new paradigm we make our binaries available for others on the web. Our software is structured in a way that makes experimentation easy and includes a viewer for displaying the final results.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number45873
NPARC number5765463
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Record identifier0c69baee-9039-4c81-a61d-e23182eec12c
Record created2009-03-29
Record modified2016-05-09
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