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.
|Title of host publication||International Conference on Pattern Recognition Applications And Methods|
|Number of pages||6|
|Publication status||Published - 1 Feb 2012|