Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision - Marr Prize Special Issue
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Similarity and Affine Invariant Distances Between 2D Point Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Incorporation of shape priors into geometric active contours
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Colorization using optimization
ACM SIGGRAPH 2004 Papers
Interactive Graph Cut Based Segmentation with Shape Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Improved watershed segmentation using water diffusion and local shape priors
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
An Unbiased Second-Order Prior for High-Accuracy Motion Estimation
Proceedings of the 30th DAGM symposium on Pattern Recognition
GeoS: Geodesic Image Segmentation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
POSECUT: simultaneous segmentation and 3D pose estimation of humans using dynamic graph-cuts
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
People tracking and segmentation using efficient shape sequences matching
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Interactive Image Segmentation via Adaptive Weighted Distances
IEEE Transactions on Image Processing
Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking
IEEE Transactions on Image Processing
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Image segmentation is able to provides elements for enhancing a physical real-world environment. Although many existing segmentation methods have achieved impressive performances, they face problems where multiple similar objects are in close proximity to one another. We improve geodesic distance transform and define a symmetric morphology filter for segmentation. We embed shape prior knowledge into this geodesic distance transform filter. The proposed geodesic distance transform filter considers three factors simultaneously: the geometric distance, weighted gradients, and the distance to the boundary of the shape priors. As a result, it provides segmentation in line with the real shape of a particular kind of object. Positive results are demonstrated for several images and video sequences.