Publication detail

Simple Single View Scene Calibration

PŘIBYL, B. ZEMČÍK, P.

Original Title

Simple Single View Scene Calibration

Type

conference paper

Language

English

Original Abstract

This paper addresses automatic calibration of images, where the main goal is to extract information about objects and relations in the scene based on the information contained in the image itself. The purpose of such calibration is to enable e.g. determination of object coordinates, measurements of distances or areas between objects in the image, etc. The idea of the presented work is to detect objects in the image whose size is known, e.g. traffic signs in the presented case and exploit their relative sizes and positions in the image to perform the calibration under some assumptions about possible spatial distribution of the objects, e.g. their positioning on a plane in the presented case. The paper describes related work and the method itself, shows and discusses the results and proposes possible extensions.

Keywords

Scene Calibration, Scene Reconstruction, Euclidean Reconstruction, Single View, Automatic Parameters Estimation, Principal Component Analysis

Authors

PŘIBYL, B.; ZEMČÍK, P.

RIV year

2011

Released

22. 8. 2011

Publisher

Springer Verlag

Location

Ghent

ISBN

978-3-642-23686-0

Book

Advanced Concepts for Intelligent Vision Systems

Edition

Lecture Notes in Computer Science

ISBN

0302-9743

Periodical

Lecture Notes in Computer Science

Number

6915

State

Federal Republic of Germany

Pages from

748

Pages to

759

Pages count

12

URL

http://link.springer.com/chapter/10.1007/978-3-642-23687-7_67

BibTex

@inproceedings{BUT76289,
  author="Bronislav {Přibyl} and Pavel {Zemčík}",
  title="Simple Single View Scene Calibration",
  booktitle="Advanced Concepts for Intelligent Vision Systems",
  year="2011",
  series="Lecture Notes in Computer Science",
  journal="Lecture Notes in Computer Science",
  number="6915",
  pages="748--759",
  publisher="Springer Verlag",
  address="Ghent",
  doi="10.1007/978-3-642-23687-7",
  isbn="978-3-642-23686-0",
  issn="0302-9743",
  url="http://link.springer.com/chapter/10.1007/978-3-642-23687-7_67"
}