Authors:
Osian Haines
and
Andrew Calway
Affiliation:
University of Bristol, United Kingdom
Keyword(s):
Monocular vision, Image understanding, Single image, Plane detection, Planar structure, Scene analysis, Learning, Nearest neighbour, Topic discovery, Latent semantic analysis, Spatiogram.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Image Understanding
;
Object Recognition
;
Pattern Recognition
;
Perception
;
Regression
;
Software Engineering
;
Theory and Methods
Abstract:
Outdoor urban scenes typically contain many planar surfaces, which are useful for tasks such as scene reconstruction, object recognition, and navigation, especially when only a single image is available. In such situations the lack of 3D information makes finding planes difficult; but motivated by how humans use their prior knowledge to interpret new scenes with ease, we develop a method which learns from a set of training examples, in order to identify planar image regions and estimate their orientation. Because it does not rely explicitly on rectangular structures or the assumption of a ‘Manhattan world’, our method can generalise to a variety of outdoor environments. From only one image, our method reliably distinguishes planes from non-planes, and estimates their orientation accurately; this is fast and efficient, with application to a real-time system in mind.