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Fast model tracking with multiple cameras for augmented reality

Published: 10 November 2004 Publication History

Abstract

In this paper we present a technique for tracking complex models in video sequences with multiple cameras. Our method uses information derived from image gradient by comparing them with edges of the tracked object, whose 3D model is known. A score function is defined, depending on the amount of image gradient "seen" by the model edges. The sought pose parameters are obtained by maximizing this function using a non deterministic algorithm which proved to be optimal for this problem. Preliminary experiments with both synthetic and real sequences have shown small errors in pose estimations and a good behavior in augmented reality applications.

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cover image ACM Conferences
VRST '04: Proceedings of the ACM symposium on Virtual reality software and technology
November 2004
226 pages
ISBN:1581139071
DOI:10.1145/1077534
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 10 November 2004

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  1. exterior orientation
  2. pose estimation
  3. registration

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