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Conditions for segmentation of motion with affine fundamental matrix

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Main Authors: Shafriza Nisha, Basah, Dr., Hoseinnezhad, Reza, Bab-Hadiashar, Alireza
Other Authors: sbasah@swin.edu.au
Format: Article
Language:English
Published: Springer-Verlag Berlin Heidelberg 2014
Subjects:
Fundamental matrix
Motion segmentation
Segmentation of motions
Computer vision problems
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33925
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spelling my.unimap-339252014-04-23T01:15:13Z Conditions for segmentation of motion with affine fundamental matrix Shafriza Nisha, Basah, Dr. Hoseinnezhad, Reza Bab-Hadiashar, Alireza sbasah@swin.edu.au rezah@unimelb.edu.au abab-hadiashar@swin.edu.au Fundamental matrix Motion segmentation Segmentation of motions Computer vision problems Link to publisher's homepage at http://link.springer.com/ Various computer vision applications involve recovery and estimation of multiple motions from images of dynamic scenes. The exact nature of objects’ motions and the camera parameters are often not known a priori and therefore, the most general motion model (the fundamental matrix) is applied. Although the estimation of a fundamental matrix and its use for motion segmentation are well understood, the conditions governing the feasibility of segmentation for different types of motions are yet to be discovered. In this paper, we study the feasibility of separating a motion (of a rigid 3D object) with affine fundamental matrix in a dynamic scene from another similar motion (unwanted motion).We show that successful segmentation of the target motion depends on the difference between rotation angles and translational directions, the location of points belonging to the unwanted motion, the magnitude of the unwanted translation viewed by a particular camera and the level of noise. Extensive set of controlled experiments using synthetic images were conducted to show the validity of the proposed constraints. The similarity between the experimental results and the theoretical analysis verifies the conditions for segmentation of motion with affine fundamental matrix. These results are important for practitioners designing solutions for computer vision problems. 2014-04-23T01:15:13Z 2014-04-23T01:15:13Z 2009 Article Advances in Visual Computing, vol. 5875, 2009, pages 415-424 3642103308;978-364210330-8 03029743 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33925 http://link.springer.com/chapter/10.1007%2F978-3-642-10331-5_39 10.1007/978-3-642-10331-5_39 en Springer-Verlag Berlin Heidelberg
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Fundamental matrix
Motion segmentation
Segmentation of motions
Computer vision problems
spellingShingle Fundamental matrix
Motion segmentation
Segmentation of motions
Computer vision problems
Shafriza Nisha, Basah, Dr.
Hoseinnezhad, Reza
Bab-Hadiashar, Alireza
Conditions for segmentation of motion with affine fundamental matrix
description Link to publisher's homepage at http://link.springer.com/
author2 sbasah@swin.edu.au
author_facet sbasah@swin.edu.au
Shafriza Nisha, Basah, Dr.
Hoseinnezhad, Reza
Bab-Hadiashar, Alireza
format Article
author Shafriza Nisha, Basah, Dr.
Hoseinnezhad, Reza
Bab-Hadiashar, Alireza
author_sort Shafriza Nisha, Basah, Dr.
title Conditions for segmentation of motion with affine fundamental matrix
title_short Conditions for segmentation of motion with affine fundamental matrix
title_full Conditions for segmentation of motion with affine fundamental matrix
title_fullStr Conditions for segmentation of motion with affine fundamental matrix
title_full_unstemmed Conditions for segmentation of motion with affine fundamental matrix
title_sort conditions for segmentation of motion with affine fundamental matrix
publisher Springer-Verlag Berlin Heidelberg
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33925
_version_ 1643797348665524224
score 13.222552

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