Multi-view random fields and street-side imagery
Date issued
2012
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Václav Skala - UNION Agency
Abstract
In this paper, we present a method that introduces graphical models into a multi-view scenario. We focus on a
popular Random Fields concept that many researchers use to describe context in a single image and introduce a
new model that can transfer context directly between matched images – Multi-View Random Fields. This
method allows sharing not only visual information between images, but also contextual information for the
purpose of object recognition and classification. We describe the mathematical model for this method as well as
present the application for a domain of street-side image datasets. In this application, the detection of façade
elements has improved by up to 20% using Multi-view Random Fields.
Description
Subject(s)
náhodná pole, grafické modely, multi-view scénáře, počítačové vidění
Citation
Journal of WSCG. 2012, vol. 20, no. 2, p. 137-144.