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Limits of motion-background segmentation using fundamental matrix estimation

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conference contribution
posted on 2024-07-12, 15:46 authored by Shafriza Nisha Basah, Reza Hoseinnezhad, Alireza Bab-Hadiashar
Images of a moving object acquired by a static camera typically contain two groups of image correspondences belonging to the object in motion and the static (or nearly static) background. For objects with relatively small motion, there is little distinction between the effect of motion and the background noise. As the type of motion is also not known in advance, the fundamental matrix motion model is usually applied in most vision algorithms. In this paper, we study the separability of a small motion from the static background via fundamental matrix estimation and introduce the necessary conditions for successful motion-background separation. We show that a pure translational motion in the above framework is inseparable from the static background regardless of its magnitude. An extensive set of controlled experiments have been conducted to validate the findings and to quantify the necessary condition (in terms of the rotational angle) for successful separation of a general motion from a static background.

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ISBN

9780769534565

Conference name

Digital Image Computing: Techniques and Applications Conference, DICTA 2008, Canberra, Australia, 01-03 December 2008

Pagination

6 pp

Publisher

IEEE

Copyright statement

Copyright © 2008 IEEE. The published version is reproduced in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Language

eng

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