3DPO: A three-dimensional part orientation system
International Journal of Robotics Research
Incremental reconstruction of 3D scenes from multiple, complex images
Artificial Intelligence
Structural Stereopsis for 3-D Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Computer Vision
Computational strategies for object recognition
ACM Computing Surveys (CSUR)
A Bayesian compatibility model for graph matching
Pattern Recognition Letters
Structural Matching by Discrete Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Epipolar Geometry and Linear Subspace Methods: A New Approach to Weak Calibration
International Journal of Computer Vision
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uncertainty Propagation and the Matching of Junctions as Feature Groupings
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Geometry and Matching of Lines and Curves Over Multiple Views
International Journal of Computer Vision
Structural Graph Matching Using the EM Algorithm and Singular Value Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Symbol Recognition by Error-Tolerant Subgraph Matching between Region Adjacency Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Algorithmics and applications of tree and graph searching
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Qualitative Scene Interpretation Using Planar Surfaces
Autonomous Robots
On Standard Quadratic Optimization Problems
Journal of Global Optimization
M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-Primitive Hierarchical (MPH) Stereo Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Least Committment Graph Matching by Evolutionary Optimisation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
A Complementary Pivoting Approach to Graph Matching
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Fast Winner-Takes-All Networks for the Maximum Clique Problem
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Image matching with scale adjustment
Computer Vision and Image Understanding
A Unifying Framework for Relational Structure Matching
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Common subgraph isomorphism detection by backtracking search
Software—Practice & Experience
Shape modeling and matching in identifying protein structure from low-resolution images
Proceedings of the 2007 ACM symposium on Solid and physical modeling
Shape modeling and matching in identifying 3D protein structures
Computer-Aided Design
International Journal of Robotics Research
Graph matching using the interference of continuous-time quantum walks
Pattern Recognition
On parameterized complexity of the Multi-MCS problem
Theoretical Computer Science
A game-theoretic approach to partial clique enumeration
Image and Vision Computing
Graph matching using the interference of discrete-time quantum walks
Image and Vision Computing
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Real-time systems: incomplete solution approach for the maximum-weighted clique problem
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Logic programming for combinatorial problems
Artificial Intelligence Review
Clustering graphs for visualization via node similarities
Journal of Visual Languages and Computing
Orthonormal Kernel Kronecker product graph matching
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
A continuous-based approach for partial clique enumeration
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Effective corner matching for transformed image identification
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
A new spectral bound on the clique number of graphs
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
A new approach to corner matching from image sequence using fuzzy similarity index
Pattern Recognition Letters
Improving the maximum-weight clique algorithm for the dense graphs
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Graph-based quadratic optimization: A fast evolutionary approach
Computer Vision and Image Understanding
Graph attribute embedding via Riemannian submersion learning
Computer Vision and Image Understanding
Listing all maximal cliques in large sparse real-world graphs
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
Geometric graph comparison from an alignment viewpoint
Pattern Recognition
A spectral-multiplicity-tolerant approach to robust graph matching
Pattern Recognition
Journal of Visual Communication and Image Representation
| Hi-index | 0.15 |
The authors propose a method for solving the stereo correspondence problem. The method consists of extracting local image structures and matching similar such structures between two images. Linear edge segments are extracted from both the left and right images. Each segment is characterized by its position and orientation in the image as well as its relationships with the nearby segments. A relational graph is thus built from each image. For each segment in one image as set of potential assignments is represented as a set of nodes in a correspondence graph. Arcs in the graph represent compatible assignments established on the basis of segment relationships. Stereo matching becomes equivalent to searching for sets of mutually compatible nodes in this graph. Sets are found by looking for maximal cliques. The maximal clique best suited to represent a stereo correspondence is selected using a benefit function. Numerous results obtained with this method are shown.