skip to main content
10.1145/2072298.2072422acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
short-paper

From images to 3d models made easy

Published: 28 November 2011 Publication History

Abstract

FIT3D is a Toolbox built for Matlab that aims at unifying and distributing a set of tools that will allow the researcher to obtain a complete 3D model from a set of calibrated images. In this paper we motivate and present the structure of the toolbox in a tutorial and example based approach. Given its exibility and scope we believe that FIT3D represents an exciting opportunity for researchers that want to develop or test one particular method with real data without the need for extensive additional programming.

References

[1]
J. Bouguet. Camera calibration toolbox for matlab. ttp://www.vision.caltech.edu/bouguetj/.
[2]
Frank Dellaert, Steven Seitz, Chuck Thorpe, and ebastian Thrun. Structure from motion without orrespondence. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition ( CVPR'00 ), June 2000.
[3]
I. Esteban, J. Dijk, and F.C.A. Groen. Fit3d toolbox: multiple view geometry and 3d reconstruction for matlab. In International Symposium on Security and Defence Europe (SPIE), 2010.
[4]
Isaac Esteban, Judith Dijk, and F.C.A. Groen. Automatic 3d reconstruction of the urban landscape. In ICUMT, 2010.
[5]
Isaac Esteban, Leo Dorst, and Judith Dijk. Closed form solution for the scale ambiguity problem in monocular visual odometry. In ICIRA, 2010.
[6]
Y. Furukawa and J. Ponce. Accurate, dense, and robust multi-view stereopsis. In Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on, pages 1--8, 2007.
[7]
R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, ISBN: 0521623049, 2000.
[8]
P. D. Kovesi. MATLAB and Octave functions for computer vision and image processing. School of Computer Science & Software Engineering, The University of Western Australia. Available from: http://www.csse.uwa.edu.au/~pk/research/matlabfns/.
[9]
M.I.A. Lourakis and A.A. Argyros. The design and implementation of a generic sparse bundle adjustment software package based on the levenberg-marquardt algorithm. Technical Report 340, Institute of Computer Science - FORTH, Heraklion, Crete, Greece, Aug. 2004. Available from http://www.ics.forth.gr/~lourakis/sba.
[10]
D. Lowe. Distinctive image features from scale-invariant keypoints. In Int. J. of Computer Vision, 2004.
[11]
D. Nister. An efficient solution to the five-point relative pose problem. In CVPR, 2003.
[12]
Noah Snavely, Steven M. Seitz, and Richard Szeliski. Photo tourism: Exploring photo collections in 3d. In SIGGRAPH Conference Proceedings, pages 835--846, New York, NY, USA, 2006. ACM Press.
[13]
@A. Vedaldi. An open implementation of the SIFT detector and descriptor. Technical Report 070012, UCLA CSD, 2007.

Cited By

View all
  • (2021)An Automatic 3D Scene Generation Pipeline Based on a Single 2D ImageAugmented Reality, Virtual Reality, and Computer Graphics10.1007/978-3-030-87595-4_9(109-117)Online publication date: 16-Sep-2021

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
MM '11: Proceedings of the 19th ACM international conference on Multimedia
November 2011
944 pages
ISBN:9781450306164
DOI:10.1145/2072298
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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2011

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. 3D modeling
  2. matlab
  3. reconstruction
  4. structure from motion
  5. vision

Qualifiers

  • Short-paper

Conference

MM '11
Sponsor:
MM '11: ACM Multimedia Conference
November 28 - December 1, 2011
Arizona, Scottsdale, USA

Acceptance Rates

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2021)An Automatic 3D Scene Generation Pipeline Based on a Single 2D ImageAugmented Reality, Virtual Reality, and Computer Graphics10.1007/978-3-030-87595-4_9(109-117)Online publication date: 16-Sep-2021

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media