Window Detection in Facades

This work is about a novel methodology for window detection in urban environments and its multiple use in vision system applications. The presented method for window detection includes appropriate early image processing, provides a multi-scale Haar wavelet representation for the determination of image tiles which is then fed into a cascaded classifier for the task of window detection. The classifier is learned from a Gentle Adaboost driven cascaded decision tree [1] on masked information from training imagery and is tested towards window based ground truth information which is - together with the original building image databases - publicly available [10, 11, 13]. The experimental results demonstrate that single window detection is to a sufficient degree successful, e.g., for the purpose of building recognition, and, furthermore, that the classifier is in general capable to provide a region of interest operator for the interpretation of urban environments. The extraction of this categ...

• Type: Conference
• Year: 2007
• Where: ICIAP
• Authors: Haider Ali, Christin Seifert, Nitin Jindal, Lucas Paletta, Gerhard Paar
• Keywords: ICIAP 2007, Image Processing, Single Window Detection, Window Based Ground, Window Detection