Interpreting line drawings of curved objects
Interpreting line drawings of curved objects
Recognizing corners by fitting parametric models
International Journal of Computer Vision
Following corners on curves and surfaces in the scale space
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
An Active Testing Model for Tracking Roads in Satellite Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active fixation for scene exploration
International Journal of Computer Vision - Special issue: machine vision research at the Royal Institute of Technology
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Junctions: Detection, Classification, and Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Low Level Feature Extraction
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
On Binocularly Viewed Occlusion Junctions
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Visual Deconstruction: Recognizing Articulated Objects
EMMCVPR '97 Proceedings of the First International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Twenty Questions, Focus of Attention, and A*: A Theoretical Comparison of Optimization Strategies
EMMCVPR '97 Proceedings of the First International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Segmentation by Grouping Junctions
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Junction and corner detection through the extraction and analysis of line segments
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
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In this paper, we propose two Bayesian methods for detecting and grouping junctions. Our junction detection method evolves from the Kona approach, and it is based on a competitive greedy procedure inspired in the region competition method. Then, junction grouping is accomplished by finding connecting paths between pairs of junctions. Path searching is performed by applying a Bayesian A*algorithm that has been recently proposed. Both methods are efficient and robust, and they are tested with synthetic and real images.