Detecting windows in city scenes

Björn Johansson, Fredrik Kahl

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

In this paper we present an object detection system for city environments. We focus on the problem of automatically detecting windows on buildings. Several possible applications for the detection system are given, such as recognition of buildings, pose estimation, rectification and 3D reconstruction. Experimental validations on real images are also provided. The system is capable of detecting windows in images at several different orientations and scales. The approach is based on learning from examples using support vector machines. Since the system is trainable, the extension to detect other objects in the scene is straightforward. The performance of the system has been evaluated on an independent training set and the results show that the object category "window" can be reliably detected under various poses and lighting conditions.
Original languageEnglish
Title of host publicationPattern Recognition with Support Vector Machines. First International Workshop, SVM 2002. Proceedings (Lecture Notes in Computer Science Vol.2388)
PublisherSpringer
Pages388-396
Volume2388
ISBN (Print)3-540-44016-X
Publication statusPublished - 2002
EventPattern Recognition with Support Vector Machines. First International Workshop, SVM 2002 - Niagara Falls, Ont., Canada
Duration: 2002 Aug 10 → …

Publication series

Name
Volume2388
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferencePattern Recognition with Support Vector Machines. First International Workshop, SVM 2002
Country/TerritoryCanada
CityNiagara Falls, Ont.
Period2002/08/10 → …

Subject classification (UKÄ)

  • Mathematical Sciences

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