Choosing nodes in parametric curve interpolation
Computer-Aided Design
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
A robust algorithm for image principal curve detection
Pattern Recognition Letters
Guided-MLESAC: Faster Image Transform Estimation by Using Matching Priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized Principal Component Analysis (GPCA)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting B-spline curves to point clouds by curvature-based squared distance minimization
ACM Transactions on Graphics (TOG)
Nonlinear Mean Shift for Clustering over Analytic Manifolds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Robust Multiple Structures Estimation with J-Linkage
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Nonparametric estimation of multiple structures with outliers
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Detection of electrophysiology catheters in noisy fluoroscopy images
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Energy-Based Geometric Multi-model Fitting
International Journal of Computer Vision
Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Enhancement of Low-Contrast Curvilinear Features in Imagery
IEEE Transactions on Image Processing
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The detection of multiple complex structures in noisy, outlier-rich two- and three-dimensional data is a challenging model estimation problem. In this paper, we build on the RANSAC method to select multiple model instances, focusing especially on curve estimation. Estimation of complex curves such as splines has so far received little attention in the context of model estimation, but has primarily been considered as a segmentation problem. Our proposed curve estimation is based on Sparse-Plus-Dense RANSAC, a framework in which estimation is performed on sparse points, guided by dense image data. This approach is extended to complex curvilinear models, in two- and three-dimensional data. The estimation is hierarchical, based on a merging step that uses an intuitive cost function. Results are presented on synthetic and real X-ray data, showing that the proposed approach performs comparably to state-of-the-art multiple model estimation in the synthetic data, while it significantly outperforms state-of-the-art in the real X-ray sequences. It also achieves correct localization of the model endpoints, which is a crucial aspect in the context of the clinical application.