International Journal of Computer Vision
Personnel tracking on construction sites using video cameras
Advanced Engineering Informatics
Computer Vision and Image Understanding
Robust wide baseline scene alignment based on 3D viewpoint normalization
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Image Guided Reconstruction of Un-sampled Data: A Filling Technique for Cultural Heritage Models
International Journal of Computer Vision
A systematic approach for 2D-image to 3D-range registration in urban environments
Computer Vision and Image Understanding
Fast and robust semi-automatic registration of photographs to 3D geometry
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
Automatic fusion of digital images and laser scanner data for heritage preservation
EuroMed'12 Proceedings of the 4th international conference on Progress in Cultural Heritage Preservation
Automatic registration of large-scale multi-sensor datasets
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
Fully Automatic Registration of Image Sets on Approximate Geometry
International Journal of Computer Vision
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The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates multiview geometry and automated 3D registration techniques for texture mapping 2D images onto 3D range data. The 3D range scans and the 2D photographs are respectively used to generate a pair of 3D models of the scene. The first model consists of a dense 3D point cloud, produced by using a 3D-to-3D registration method that matches 3D lines in the range images. The second model consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. This paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes.