Abstract—Identification of building façades from digital images is one of the central problems in mobile augmented reality (MAR) applications in the built environment. Directly analyzing the whole image can increase the difficulty of façade identification due to the presence of image portions which are not façade. This paper presents an automatic approach to façade region detection given a single street view image as a pre-processing step to subsequent steps of façade identification. We devise a coarse façade region detection method based on the observation that façades are image regions with repetitive patterns containing a large amount of vertical and horizontal line segments. Firstly, scan lines are constructed from vanishing points and center points of image line segments. Hue profiles along these lines are then analyzed and used to decompose the image into rectilinear patches with similar repetitive patterns. Finally, patches are merged into larger coherent regions and the main building façade region is chosen based on the occurrence of horizontal and vertical line segments within each of the merged regions. A validation of our method showed that on average façade regions are detected in conformity with manually segmented images as ground truth.
Index Terms—façade region detection, street view image, vanishing point, mobile augmented reality
Cite: Fei Liu and Stefan Seipel, "Detection of Façade Regions in Street View Images from Split-and-Merge of Perspective Patches," Journal of Image and Graphics, Vol. 2, No. 1, pp. 8-14, June 2014. doi: 10.12720/joig.2.1.8-14
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