Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures
Journal of Mathematical Imaging and Vision
Image segmentation by clustering of spatial patterns
Pattern Recognition Letters
Journal of Mathematical Imaging and Vision
Locally regularized smoothing B-snake
EURASIP Journal on Applied Signal Processing
Automatic Guidance of an Ultrasound Probe by Visual Servoing Based on B-Mode Image Moments
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
International Journal of Computer Vision
Region-Based Active Contours with Exponential Family Observations
Journal of Mathematical Imaging and Vision
Multiphase active contour segmentation constrained by evolving medial axes
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Polar snakes: a fast and robust parametric active contour model
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
IFTrace: Video segmentation of deformable objects using the Image Foresting Transform
Computer Vision and Image Understanding
Tensor-SIFT Based Earth Mover's Distance for Contour Tracking
Journal of Mathematical Imaging and Vision
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This paper deals with fast image and video segmentation using active contours. Region-based active contours using level sets are powerful techniques for video segmentation, but they suffer from large computational cost. A parametric active contour method based on B-Spline interpolation has been proposed in to highly reduce the computational cost, but this method is sensitive to noise. Here, we choose to relax the rigid interpolation constraint in order to robustify our method in the presence of noise: by using smoothing splines, we trade a tunable amount of interpolation error for a smoother spline curve. We show by experiments on natural sequences that this new flexibility yields segmentation results of higher quality at no additional computational cost. Hence, real-time processing for moving objects segmentation is preserved.