Detecting planes and estimating their orientation from a single image

Osian Haines, Andrew Calway

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

11 Citations (Scopus)


We propose an algorithm to detect planes in a single image of an outdoor urban scene, capable of identifying multiple distinct planes, and estimating their orientation. Using machine learning techniques, we learn the relationship between appearance and structure from a large set of labelled examples. Plane detection is achieved by classifying multiple overlapping image regions, in order to obtain an initial estimate of planarity for a set of points, which are segmented into planar and non-planar regions using a sequence of Markov random fields. This differs from previous methods in that it does not rely on line detection, and is able to predict an actual orientation for planes. We show that the method is able to reliably extract planes in a variety of scenes, and compares favourably with existing methods.
Original languageUndefined/Unknown
Title of host publicationBritish Machine Vision Conference
Publication statusPublished - 1 Sep 2012

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