Abstract
Abstract. To reconstruct 3D building models, building footprints and heights are essential information. From OpenStreetMap (OSM), we can easily obtain footprints. However, building height is usually missing. In order to yield the height information of building in OSM, this paper proposes a geometric method to estimate building height from geotagged photographs. This method explores the geometric relationship between the perspective centre of geotagged photos and buildings. Through matching photos and OSM, building height can be estimated according to the ratio of height to width of building. The proposed method can be divided into three parts. First, automatic geometric correction of photos is realized by using vanishing point tracking. After that, a semi-automatic scene search method is proposed to match the geotagged photograph and OSM. In this step, geographic coordinates of photos are used to locate a photographic scene. According to the edge of the building in the photos, corresponding footprints in OSM can be found. Finally, based on the length of the associated edge in the building footprint in OSM, the height of building can be calculated. Using Flickr photos and OSM in London, we experiment with the proposed method. The robustness of the geometric model has been verified. Experiments show that the proposed method is pertinent as the estimated height has expressed a proper ratio with its width, which is the same as the corrected photos. In particular for automatic geometric correction, which can achieve the same good results as the correction of manual operation.
Highlights
With citizens as sensors, Volunteered geographic information (VGI) (Goodchild, 2007) provides us with massive data for updating and reconstructing three-dimensional building models worldwide (Over et al 2010, Bagheri et al, 2019)
It is known that OSM can provide building footprints, which is a vector element formed by a two-dimensional outline of building
The relative position of the perspective centre is estimated by combining vanishing points and image line features
Summary
With citizens as sensors, Volunteered geographic information (VGI) (Goodchild, 2007) provides us with massive data for updating and reconstructing three-dimensional building models worldwide (Over et al 2010, Bagheri et al, 2019). One difficulty is how to accurately obtain building height In existing methods, such as extracting height information from multi-source sensor data is reliable. This method requires professional data collection, such as oblique photogrammetry, which is a large workload for urban 3D reconstructing Another method is to extract the height information of buildings from geotagged photos. Sihombing et al (2016) propose the method of correcting license plate image with plane homography matrix. This method takes advantage of fixed size of license plate and fixed ratio of length to width. Habib (2003) propose a calibration method for low-cost camera This method first extracts lines in an image, and establishes a test field to calculate distortion parameters of this image.
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