Abstract
An increasing number of applications require 3D content. However, its creation from real-world data either necessitates expensive equipment, artistic skills, or is constrained, for example, by the range of the utilized sensors. Image-based modeling is rapidly increasing in popularity since cameras are very affordable, widely available, and have a wide image acquisition range suitable for objects of vastly different size. The technique is especially suitable for mobile robotics involving low cost equipment and robots with a light payload, for example, small UAVs. In this paper we describe a novel image-based modeling system, which produces high-quality 3D content automatically from a collection of unconstrained and uncalibrated 2D images. The system estimates camera parameters and a 3D scene geometry using Structure-from-Motion (SfM) and Bundle Adjustment techniques. The point cloud density of 3D scene components is enhanced by exploiting silhouette information of the scene. This hybrid approach dramatically improves the reconstruction of objects with few visual features, for example, unicolored objects, and improves surface smoothness. A high quality texture is created by parameterizing the reconstructed objects using a segmentation and charting approach which also works for objects which are not homeomorphic to a sphere. The resulting parameter space contains one chart for each surface segment. A texture map is created by back projecting the best fitting input images onto each surface segment, and smoothly fusing them together over the corresponding chart by using graph-cut techniques.
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