Solid shape
The design and analysis of spatial data structures
The design and analysis of spatial data structures
Robust regression methods for computer vision: a review
International Journal of Computer Vision
A theory of self-calibration of a moving camera
International Journal of Computer Vision
Geometric invariance in computer vision
Geometric invariance in computer vision
Rapid octree construction from image sequences
CVGIP: Image Understanding
Object-centered surface reconstruction: combining multi-image stereo and shading
International Journal of Computer Vision
Motion Estimation with Quadtree Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Progressive simplicial complexes
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
From Multiple Stereo Views to Multiple 3-D Surfaces
International Journal of Computer Vision
A Pixel Dissimilarity Measure That Is Insensitive to Image Sampling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelets for computer graphics: theory and applications
Wavelets for computer graphics: theory and applications
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Non-parametric Local Transforms for Computing Visual Correspondence
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Complete Dense Stereovision Using Level Set Methods
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Changes in Surface Convexity and Topology Caused by Distortions of Stereoscopic Visual Space
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Photorealistic Scene Reconstruction by Voxel Coloring
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Ordinal Measures for Visual Correspondence
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
3-D Scene Data Recovery using Omnidirectional Multibaseline Stereo
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Space-Sweep Approach to True Multi-Image Matching
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Stereo Matching with Transparency and Matting
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Constructing Virtual Worlds Using Dense Stereo
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
What Does the Scene Look Like from a Scene Point?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
A Probabilistic Theory of Occupancy and Emptiness
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Joint Multi-Layer Segmentation and Reconstruction for Free-Viewpoint Video Applications
International Journal of Computer Vision
A survey of methods for volumetric scene reconstruction from photographs
VG'01 Proceedings of the 2001 Eurographics conference on Volume Graphics
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This paper introduces a new mult-iview reconstruction problem called approximate N-view stereo. The goal of this problem is to recover a one-parameter family of volumes that are increasingly tighter supersets of an unknown, arbitrarily-shaped 3D scene. By studying 3D shapes that reproduce the input photographs up to a special image transformation called a shuffle transformation, we prove that (1) these shapes can be organized hierarchically into nested supersets of the scene, and (2) they can be computed using a simple algorithm called Approximate Space Carving that is provably-correct for arbitrary discrete scenes (i.e., for unknown, arbitrarily-shaped Lambertian scenes that are defined by a finite set of voxels and are viewed from N arbitrarily-distributed viewpoints inside or around them). The approach is specifically designed to attack practical reconstruction problems, including (1) recovering shape from images with inaccurate calibration information, and (2) building coarse scene models from multiple views.