Abstract
This paper describes a method of geo-registering a sequence of panoramic images to a digital map by matching pixel information from the images with information on the building footprint contained in a digital map. Recently, images captured at the ground level using a Mobile Mapping System (MMS), such as the panoramic images displayed by Google Street View, have been considered as a valuable resource for three-dimensional (3D) building modeling. However, the wide intervals between these panoramic images, as well as locational and directional error from the related sensors, make it difficult to analyze the image data. This paper demonstrates a formulation method for connecting pixels in panoramic images with information on footprint vertices and building lines contained in a digital map. To allow both pixel and footprint information consistent in 3D space, each panoramic image is tilt-corrected in pre-processing to upright the image using the estimated pitch and roll of a vehicle and removing the pitch and roll effects from the panoramic image pixels. Through the proposed formulation, a single panoramic image can be easily geo-registered with simple user-provided constraints, and adjacent sequential images can then be automatically geo-registered using point feature matching. Experimental results showed a significant reduction in the locational and directional error of sequential panoramic images, and the proposed vanishing point (VP) based validation process was found to successfully detect failure cases.
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