A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and Vision Computing
Stereo Correspondence Through Feature Grouping and Maximal Cliques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Edge Detectors for Ramp Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Hough transform algorithm with a 2D hypothesis testing kernel
CVGIP: Image Understanding
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Matching Point Features with Ordered Geometric, Rigidity, and Disparity Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for low level feature extraction
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Hierarchical stereo and motion correspondence using feature groupings
International Journal of Computer Vision
Active tracking of foveated feature clusters using affine structure
International Journal of Computer Vision
Matching feature points in image sequences through a region-based method
Computer Vision and Image Understanding
An optimizing line finder using a Hough transform algorithm
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Junctions: Detection, Classification, and Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Intensity- and Gradient-Based Stereo Matching Using Hierarchical Gaussian Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion and Structure from Image Sequences
Motion and Structure from Image Sequences
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Estimating motion and structure from correspondences of line segments between two perspective images
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Spatial-Temporal Junction Extraction and Semantic Interpretation
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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The interpretation of the 3D world from image sequences requires the identification and correspondences of key features in the scene. In this paper, we describe a robust algorithm for matching groupings of features related to the objects in the scene. We consider the propagation of uncertainty from the feature detection stage through the grouping stage to provide a measure of uncertainty at the matching stage. We focus upon indoor scenes and match junctions, which are groupings of line segments that meet at a single point. A model of the uncertainty in junction detection is described, and the junction uncertainty under the epipolar constraint is determined. Junction correspondence is achieved through matching of each line segment associated with the junction. A match likelihood is then derived based upon the detection uncertainties and then combined with information on junction topology to create a similarity measure. A robust matching algorithm is proposed and used to match junctions between pairs of images. The presented experimental results on real images show that the matching algorithm produces sufficiently reliable results for applications such as structure from motion.