文章基本信息

标题：Evaluation of the Automatic Methods for Building Extraction
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作者：Julia Åhlén ; Stefan Seipel ; Fei Liu 等
期刊名称：International Journal of Computers and Communications
印刷版ISSN：2074-1294
出版年度：2014
卷号：8
页码：171-176
出版社：University Press
摘要：Recognition of buildings is not a trivial task, yet highly demanded in many applications including augmented reality for mobile phones. Recognition rate can be increased significantly if building façade extraction will take place prior to the recognitionprocess. It is also a challenging task since eachbuilding can be viewed from different angles or under differentlighting conditions. Natural situation outdoor is when buildings are occluded by trees, street signs and other objects. This interferes for successful building façade recognition. In this paper we evaluate the knowledge based approach toautomatically segment out the whole buildingfaçade or major parts of thefaçade. This automatic building detection algorithm is then evaluated against other segmentation methods such as SIFT and vanishing point approach. This work contains two main steps: segmentation of building façades region using two different approaches and evaluation of the methods using database of reference features. Building recognition model (BRM) includes evaluation step that uses Chamfer metrics. BMR is then compared to vanishing points segmentation. In the evaluation mode, comparison of these two different segmentation methods is done using the data from ZuBuD.Reference matching is also done using Scale Invariant Feature Transform. Theresults show that the recognition rate is satisfactory for the BMR model and there is no need to extract the whole building façade for the successful recognition.
关键词：Building; extraction; recognition; Chamfer metrics;vanishing points; SIFT.