Efficient methods for point matching with known camera orientation

João F. C. Mota, Pedro M. Q. Aguiar

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The vast majority of methods that successfully recover 3D structure from 2D images hinge on a preliminary identification of corresponding feature points. When the images capture close views, e.g., in a video sequence, corresponding points can be found by using local pattern matching methods. However, to better constrain the 3D inference problem, the views must be far apart, leading to challenging point matching problems. In the recent past, researchers have then dealt with the combinatorial explosion that arises when searching among N! possible ways of matching N points. In this paper we overcome this search by making use of prior knowledge that is available in many situations: the orientation of the camera. This knowledge enables us to derive algorithms to compute point correspondences. We prove that our approach computes the correct solution when dealing with noiseless data and derive an heuristic that results robust to the measurement noise and the uncertainty in prior knowledge. Although we model the camera using orthography, our experiments illustrate that our method is able to deal with violations, including the perspective effects of general real images.

Original languageEnglish
Title of host publicationImage Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6111.
EditorsA. Campilho, M. Kamel
Number of pages10
ISBN (Electronic)9783642137723
Publication statusPublished - 2010
Event7th International Conference on Image Analysis and Recognition 2010 - Povoa de Varzim, Portugal
Duration: 21 Jun 201023 Jun 2010

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference7th International Conference on Image Analysis and Recognition 2010
Abbreviated titleICIAR 2010
CityPovoa de Varzim

ASJC Scopus subject areas

  • General Computer Science
  • Theoretical Computer Science


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