loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Wojciech Chojnacki ; Anton van den Hengel and Michael J. Brooks

Affiliation: School of Computer Science, University of Adelaide, Australia

ISBN: 972-8865-40-6

ISSN: 2184-4321

Keyword(s): Generalised principal component analysis, constrained minimisation, multi-line fitting, degenerate conic.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping ; Statistical Approach

Abstract: Generalised Principal Component Analysis (GPCA) is a recently devised technique for fitting a multi-component, piecewise-linear structure to data that has found strong utility in computer vision. Unlike other methods which intertwine the processes of estimating structure components and segmenting data points into clusters associated with putative components, GPCA estimates a multi-component structure with no recourse to data clustering. The standard GPCA algorithm searches for an estimate by minimising an appropriate misfit function. The underlying constraints on the model parameters are ignored. Here we promote a variant of GPCA that incorporates the parameter constraints and exploits constrained rather than unconstrained minimisation of the error function. The output of any GPCA algorithm hardly ever perfectly satisfies the parameter constraints. Our new version of GPCA greatly facilitates the final correction of the algorithm output to satisfy perfectly the constraints, making thi s step less prone to error in the presence of noise. The method is applied to the example problem of fitting a pair of lines to noisy image points, but has potential for use in more general multi-component structure fitting in computer vision. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.172.223.30

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Chojnacki, W.; van den Hengel, A. and J. Brooks, M. (2006). CONSTRAINED GENERALISED PRINCIPAL COMPONENT ANALYSIS. In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6; ISSN 2184-4321, pages 206-212. DOI: 10.5220/0001362102060212

@conference{visapp06,
author={Wojciech Chojnacki. and Anton {van den Hengel}. and Michael {J. Brooks}.},
title={CONSTRAINED GENERALISED PRINCIPAL COMPONENT ANALYSIS},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={206-212},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001362102060212},
isbn={972-8865-40-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - CONSTRAINED GENERALISED PRINCIPAL COMPONENT ANALYSIS
SN - 972-8865-40-6
IS - 2184-4321
AU - Chojnacki, W.
AU - van den Hengel, A.
AU - J. Brooks, M.
PY - 2006
SP - 206
EP - 212
DO - 10.5220/0001362102060212

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.
0123movie.net