Sciweavers

Share
CVPR
2010
IEEE

Detecting and Parsing Architecture at City Scale from Range Data

10 years 6 months ago
Detecting and Parsing Architecture at City Scale from Range Data
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input is a set of range measurements that cover large-scale urban environment. The desired output is a set of parse trees, such that each tree represents a semantic decomposition of a building – the nodes are roof surfaces as well as volumetric parts inferred from the observable surfaces. We model the above problem using a simple and generic grammar and use an efficient dependency parsing algorithm to generate the desired semantic description. We show how to learn the parameters of this simple grammar in order to produce correct parses of complex structures. We are able to apply our model on large point clouds and parse an entire city.
Alexander Toshev, Philippos Mordohai, Ben Taskar
Added 14 Apr 2010
Updated 14 May 2010
Type Conference
Year 2010
Where CVPR
Authors Alexander Toshev, Philippos Mordohai, Ben Taskar
Comments (0)
books