Principles of artificial intelligence
Principles of artificial intelligence
Stereo Correspondence Through Feature Grouping and Maximal Cliques
IEEE Transactions on Pattern Analysis and Machine Intelligence
A parallel thinning algorithm for medial surfaces
Pattern Recognition Letters
A New Algorithm for Error-Tolerant Subgraph Isomorphism Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm for Subgraph Isomorphism
Journal of the ACM (JACM)
A parallel 3D 12-subiteration thinning algorithm
Graphical Models and Image Processing
Multilocal creaseness based on the level-set extrinsic curvature
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skeleton Based Shape Matching and Retrieval
SMI '03 Proceedings of the Shape Modeling International 2003
Performance Evaluation of the VF Graph Matching Algorithm
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
SMI '04 Proceedings of the Shape Modeling International 2004
Curvature Maps for Local Shape Comparison
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
Salient geometric features for partial shape matching and similarity
ACM Transactions on Graphics (TOG)
Partial matching of 3D shapes with priority-driven search
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
Structural Descriptions and Inexact Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Min-Max Medial Axis Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Retrieving articulated 3-d models using medial surfaces and their graph spectra
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Computing a family of skeletons of volumetric models for shape description
GMP'06 Proceedings of the 4th international conference on Geometric Modeling and Processing
Genetic-based search for error-correcting graph isomorphism
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Inexact graph matching for structural pattern recognition
Pattern Recognition Letters
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
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In this paper, we describe a novel geometric approach in the process of recovering 3D protein structures from scalar volumes. The input to our method is a sequence of @a-helices that make up a protein, and a low-resolution protein density volume where possible locations of @a-helices have been detected. Our task is to identify the correspondence between the two sets of helices, which will shed light on how the protein folds in space. The central theme of our approach is to cast the correspondence problem as that of shape matching between the 3D volume and the 1D sequence. We model both shapes as attributed relational graphs, and formulate a constrained inexact graph matching problem. To compute the matching, we developed an optimal algorithm based on the A*-search with several choices of heuristic functions. As demonstrated in a suite of synthetic and authentic inputs, the shape-modeling approach is capable of identifying helix correspondences in noise-abundant volumes at high accuracy with minimal or no user intervention.