Retrieving images of similar geometrical configuration

Xiaolong Zhang, Baoxin Li

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

2 Scopus citations


Content Based Image Retrieval (CBIR) has been an active research field for a long time. Existing CBIR approaches are mostly based on low- to middle-level visual cues such as color or color histograms and possibly semantic relations of image regions, etc. In many applications, it may be of interest to retrieve images of similar geometrical configurations such as all images of a hallway-like view. In this paper we present our work on addressing such a task that seemingly requires 3D reconstruction from a single image. Our approach avoids explicit 3D reconstruction, which remains to be a challenge, through coding the potential relationship between the 3D structure of an image and its low-level features via a grid-based representation. We experimented with a data set of several thousands of images and obtained promising results.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings
Number of pages10
EditionPART 2
StatePublished - 2010
Event6th International, Symposium on Visual Computing, ISVC 2010 - Las Vegas, NV, United States
Duration: Nov 29 2010Dec 1 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6454 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International, Symposium on Visual Computing, ISVC 2010
Country/TerritoryUnited States
CityLas Vegas, NV

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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