Detail publikace

Real Projective Plane Mapping for Detection of Orthogonal Vanishing Points

JURÁNKOVÁ, M. HEROUT, A.

Originální název

Real Projective Plane Mapping for Detection of Orthogonal Vanishing Points

Anglický název

Real Projective Plane Mapping for Detection of Orthogonal Vanishing Points

Jazyk

en

Originální abstrakt

This paper deals with the detection of orthogonal vanishing points. The aim is to efficiently cope with the clutter edges in real-life images and to determine the camera orientation in the Manhattan world reliably. We are using a modified scheme of the Cascaded Hough Transform where only one Hough space is accumulated - the space of the vanishing points. The parameterization of the vanishing points - the "diamond space" - is based on the PClines line parameterization and it is defined as a mapping of the whole real projective plane to a finite space. Our parameterization of vanishing points is in all aspects linear; it involves no goniometric or other non-linear operations and thus it is suitable for implementation in embedded chips and circuitry. 

Anglický abstrakt

This paper deals with the detection of orthogonal vanishing points. The aim is to efficiently cope with the clutter edges in real-life images and to determine the camera orientation in the Manhattan world reliably. We are using a modified scheme of the Cascaded Hough Transform where only one Hough space is accumulated - the space of the vanishing points. The parameterization of the vanishing points - the "diamond space" - is based on the PClines line parameterization and it is defined as a mapping of the whole real projective plane to a finite space. Our parameterization of vanishing points is in all aspects linear; it involves no goniometric or other non-linear operations and thus it is suitable for implementation in embedded chips and circuitry. 

Dokumenty

BibTex


@inproceedings{BUT103536,
  author="Markéta {Juránková} and Adam {Herout}",
  title="Real Projective Plane Mapping for Detection of Orthogonal Vanishing Points",
  annote="This paper deals with the detection of orthogonal vanishing points. The aim is to
efficiently cope with the clutter edges in real-life images and to determine the
camera orientation in the Manhattan world reliably. We are using a modified
scheme of the Cascaded Hough Transform where only one Hough space is accumulated
- the space of the vanishing points. The parameterization of the vanishing points
- the "diamond space" - is based on the PClines line parameterization and it is
defined as a mapping of the whole real projective plane to a finite space. Our
parameterization of vanishing points is in all aspects linear; it involves no
goniometric or other non-linear operations and thus it is suitable for
implementation in embedded chips and circuitry. ",
  address="The British Machine Vision Association and Society for Pattern Recognition",
  booktitle="Proceedings of BMVC 2013",
  chapter="103536",
  doi="10.5244/C.27.90",
  edition="NEUVEDEN",
  howpublished="online",
  institution="The British Machine Vision Association and Society for Pattern Recognition",
  year="2013",
  month="july",
  pages="1--10",
  publisher="The British Machine Vision Association and Society for Pattern Recognition",
  type="conference paper"
}