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We present an interactive system for generating photorealistic, textured, piecewise-planar 3D models of architectural structures and urban scenes from unordered sets of photographs. To reconstruct 3D geometry in our system, the user draws outlines overlaid on 2D photographs. The 3D structure is then automatically computed by combining the 2D interaction(More)
We present a novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs. First a discrete set of 3D plane candidates are computed based on a sparse point cloud of the scene (recovered by structure from motion) and sparse 3D line segments reconstructed from multiple(More)
— Simultaneous localization and mapping (SLAM) is a method that robots use to explore, navigate, and map an unknown environment. However, this method poses inherent problems with regard to cost and time. To lower computation costs, smoothing and mapping (SAM) approaches have shown some promise, and they also provide more accurate solutions than filtering(More)
We present a new structure from motion (Sfm) technique based on point and vanishing point (VP) matches in images. First, all global camera rotations are computed from VP matches as well as relative rotation estimates obtained from pairwise image matches. A new multi-staged linear technique is then used to estimate all camera translations and 3D points(More)
Most existing structure from motion (SFM) approaches for unordered images cannot handle multiple instances of the same structure in the scene. When image pairs containing different instances are matched based on visual similarity , the pairwise geometric relations as well as the correspondences inferred from such pairs are erroneous, which can lead to(More)
Large-scale 3D reconstruction has recently received much attention from the computer vision community. Bundle adjustment is a key component of 3D reconstruction problems. However, traditional bundle adjustment algorithms require a considerable amount of memory and computational resources. In this paper, we present an extremely efficient, inherently(More)
In this paper, we present results and experiments with several methods for bundle adjustment, producing the fastest bundle adjuster ever published in terms of computation and convergence. From a computational perspective, the fastest methods naturally handle the block-sparse pattern that arises in a reduced camera system. Adapting to the naturally arising(More)
We present a technique for fast Poisson blending and gradient domain compositing. Instead of using a single piecewise-smooth offset map to perform the blending, we associate a separate map with each input source image. Each individual offset map is itself smoothly varying and can therefore be represented using a low-dimensional spline. The resulting linear(More)
Volumetric structures are frequently used as shape descrip-tors for 3D data. The capture of such data is being facilitated by developments in multi-view video and range scanning, extending to subjects that are alive and moving. In this paper, we examine vision-based model-ing and the related representation of moving articulated creatures using spines. We(More)