IEEE Transactions on Pattern Analysis and Machine Intelligence
A new approach to the maximum-flow problem
Journal of the ACM (JACM)
Analysis of preflow push algorithms for maximum network flow
SIAM Journal on Computing
A Fast Line Finder for Vision-Guided Robot Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Object Recognition Using Bipartite Matching Embedded in Discrete Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Closed-Form Solutions for Physically Based Shape Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Nonrigid Motion and Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-based correspondence: an eigenvector approach
Image and Vision Computing - Special issue: BMVC 1991
Model dependent inference of three-dimensional information from a sequence of two-dimensional images
Model dependent inference of three-dimensional information from a sequence of two-dimensional images
A bipartite matching approach to feature correspondence in stereo vision
Pattern Recognition Letters
The ascender system: automated site modeling from multiple aerial images
Computer Vision and Image Understanding
Data structures for weighted matching and nearest common ancestors with linking
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
Network Flows and Matching: First DIMACS Implementation Challenge
Network Flows and Matching: First DIMACS Implementation Challenge
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Corresponding Points Based on Bayesian Triangulation
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Graph matching by graduated assignment
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Determining Correspondences and Rigid Motion of 3-D Point Sets with Missing Data
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)
Site model acquisition and extension from aerial images
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Acquisition of 3D Models from a Set of 2D Images TITLE2:
Acquisition of 3D Models from a Set of 2D Images TITLE2:
A Maximum-Flow Formulation of the N-Camera Stereo Correspondence Problem
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Exploring artificial intelligence in the new millennium
Robot control via region-based 3d reconstruction
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
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Three-dimensional reconstruction from a set of images is an important and difficult problem in computer vision. In this paper, we address the problem of determining image feature correspondences while simultaneously reconstructing the corresponding 3D features, given the camera poses of disparate monocular views. First, two new affinity measures are presented that capture the degree to which candidate features from different images consistently represent the projection of the same 3D point or 3D line. An affinity measure for point features in two different views is defined with respect to their distance from a hypothetical projected 3D pseudo-intersection point. Similarly, an affinity measure for 2D image line segments across three views is defined with respect to a 3D pseudo-intersection line. These affinity measures provide a foundation for determining unknown correspondences using weighted bipartite graphs representing candidate point and line matches across different images. As a result of this graph representation, a standard graph-theoretic algorithm can provide an optimal, simultaneous matching and triangulation of points across two views, and lines across three views. Experimental results on synthetic and real data demonstrate the effectiveness of the approach.