Robust Contour Decomposition Using a Constant Curvature Criterion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Finding with Parametrically Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Face Recognition Using Active Appearance Models
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Correction for the Dislocation of Curved Surfaces Caused by the PSF in 2D and 3D CT Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
The Photographer's Eye: Composition and Design for Better Digital Photos
The Photographer's Eye: Composition and Design for Better Digital Photos
Distance regularized level set evolution and its application to image segmentation
IEEE Transactions on Image Processing
OSCAR: On-Site Composition and Aesthetics Feedback Through Exemplars for Photographers
International Journal of Computer Vision
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
International Journal of Robotics Research
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We present a novel approach for fitting a geometric shape in images. Similar to active shape models and active contours, a force field is used in our approach. But the object to be detected is described with a geometric shape, represented by parametric equations. Our model associates each parameter of this geometric shape with a combination of integrals (summations in the discrete case) of the force field along the contour. By iteratively updating the shape parameters according to these integrals, we are able to find the optimal fit of the shape in the image. In this paper, we first explore simple cases such as fitting a line, circle, ellipse or cubic spline contour using this approach. Then we employ this technique to detect the cross-sections of subarachnoid spaces containing cerebrospinal fluid (CSF) in phase-contrast magnetic resonance (PC-MR) images, where the object of interest can be described by a distorted ellipse. The detection results can be further used by an s-t graph cut to generate a segmentation of the CSF structure. We demonstrate that, given a properly configured geometric shape model and force field, this approach is robust to noise and defects (disconnections and non-uniform contrast) in the image. By using a geometric shape model, this approach does not rely on large training datasets, and requires no manual labeling of the training images as is needed when using point distribution models.