Algorithms for clustering data
Algorithms for clustering data
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Computational anatomy: an emerging discipline
Quarterly of Applied Mathematics - Special issue on current and future challenges in the applications of mathematics
Automatic Construction of 2D Shape Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probability Models for Clutter in Natural Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Silhouette-Based Isolated Object Recognition through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of Planar Shapes Using Geodesic Paths on Shape Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Elastic-string models for representation and analysis of planar shapes
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
On Shape of Plane Elastic Curves
International Journal of Computer Vision
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust symbolic representation for shape recognition and retrieval
Pattern Recognition
Robust symbolic representation for shape recognition and retrieval
Pattern Recognition
The one- and multi-sample problem for functional data with application to projective shape analysis
Journal of Multivariate Analysis
Activity representation using 3D shape models
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Shape Learning with Function-Described Graphs
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Unsupervised Riemannian Clustering of Probability Density Functions
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A Context Dependent Distance Measure for Shape Clustering
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Multi-Reference Shape Priors for Active Contours
International Journal of Computer Vision
Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images
International Journal of Computer Vision
Nonlinear Mean Shift over Riemannian Manifolds
International Journal of Computer Vision
Shape and texture clustering: Best estimate for the clusters number
Image and Vision Computing
Rate-invariant recognition of humans and their activities
IEEE Transactions on Image Processing
Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Extended Phase Field Higher-Order Active Contour Models for Networks
International Journal of Computer Vision
A Computational Model of Multidimensional Shape
International Journal of Computer Vision
Shape analysis of open curves in R3with applications to study of fiber tracts in DT-MRI data
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Sampling curve images to find similarities among parts of images
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
A Markov random field model for extracting near-circular shapes
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A similarity-based approach for shape classification using Aslan skeletons
Pattern Recognition Letters
A comprehensive Riemannian framework for the analysis of white matter fiber tracts
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Computer Vision and Image Understanding
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Theory of a probabilistic-dependence measure of dissimilarity among multiple clusters
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Statistical shape models using elastic-string representations
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Unsupervised clustering of shapes
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Shape matching using a binary search tree structure of weak classifiers
Pattern Recognition
Envelope detection of multi-object shapes
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
A computational approach to fisher information geometry with applications to image analysis
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Comparative analysis of kernel methods for statistical shape learning
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
Centralized and distributed task allocation in multi-robot teams via a stochastic clustering auction
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Image and Vision Computing
Detection, classification and estimation of individual shapes in 2D and 3D point clouds
Computational Statistics & Data Analysis
The mean boundary curve of anatomical objects
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Contour-based shape representation using principal curves
Pattern Recognition
Alignment and morphing for the boundary curves of anatomical organs
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Generative models for functional data using phase and amplitude separation
Computational Statistics & Data Analysis
Multimedia Databases and Data Management: A Survey
International Journal of Multimedia Data Engineering & Management
Global structure constrained local shape prior estimation for medical image segmentation
Computer Vision and Image Understanding
Statistical analysis of manual segmentations of structures in medical images
Computer Vision and Image Understanding
Journal of Multivariate Analysis
Computer Vision and Image Understanding
An Efficient Stochastic Clustering Auction for Heterogeneous Robotic Collaborative Teams
Journal of Intelligent and Robotic Systems
Decomposition and dictionary learning for 3D trajectories
Signal Processing
Hi-index | 0.14 |
Using a differential-geometric treatment of planar shapes, we present tools for: 1) hierarchical clustering of imaged objects according to the shapes of their boundaries, 2) learning of probability models for clusters of shapes, and 3) testing of newly observed shapes under competing probability models. Clustering at any level of hierarchy is performed using a mimimum variance type criterion criterion and a Markov process. Statistical means of clusters provide shapes to be clustered at the next higher level, thus building a hierarchy of shapes. Using finite-dimensional approximations of spaces tangent to the shape space at sample means, we (implicitly) impose probability models on the shape space, and results are illustrated via random sampling and classification (hypothesis testing). Together, hierarchical clustering and hypothesis testing provide an efficient framework for shape retrieval. Examples are presented using shapes and images from ETH, Surrey, and AMCOM databases.