Detection of Windows in Point Clouds of Urban Scenes

Abstract

Laser range scanners have now the ability to acquire millions of 3D points of highly detailed and geometrically complex urban sites, opening new avenues of exploration in modeling urban environments. However, raw data are dense and complex, lacking high-level descriptive power, thus revealing the need for the automatic detection of architectural objects, such as facades, windows, balconies, etc. In this paper, we describe novel algorithms for the detection of windows, which are ubiquitous in urban areas. Detecting isolated windows is a challenging problem due to the inability of the laser range sensors to acquire any data on transparent surfaces and due to the wide variability of window features. Our approach is based on the assumption that the elements (windows) are arranged in multiple unknown periodic structures making our system robust to single window detection errors. This kind of detection is essential for high-level recognition algorithms, compression methods, registration, as well as realistic visualizations.