The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Algorithm 360: shortest-path forest with topological ordering [H]
Communications of the ACM
Geometric partial differential equations and image analysis
Geometric partial differential equations and image analysis
Video matting of complex scenes
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Undirected single source shortest paths in linear time
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Improved Fast Gauss Transform and Efficient Kernel Density Estimation
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
Keyframe-based tracking for rotoscoping and animation
ACM SIGGRAPH 2004 Papers
Colorization using optimization
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2005 Papers
An Iterative Optimization Approach for Unified Image Segmentation and Matting
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Short note: O(N) implementation of the fast marching algorithm
Journal of Computational Physics
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Soft scissors: an interactive tool for realtime high quality matting
ACM SIGGRAPH 2007 papers
Image and video matting: a survey
Foundations and Trends® in Computer Graphics and Vision
An axiomatic approach to image interpolation
IEEE Transactions on Image Processing
Fast image and video colorization using chrominance blending
IEEE Transactions on Image Processing
Interactive Image Segmentation via Adaptive Weighted Distances
IEEE Transactions on Image Processing
Belief propagation optical flow for high-resolution image morphing
ACM SIGGRAPH 2010 Posters
CO3 for ultra-fast and accurate interactive segmentation
Proceedings of the international conference on Multimedia
Inference scene labeling by incorporating object detection with explicit shape model
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Proceedings of the 2011 SIGGRAPH Asia Conference
User-steered image segmentation using live markers
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Interactive image segmentation by matching attributed relational graphs
Pattern Recognition
Video composition by optimized 3D mean-value coordinates
Computer Animation and Virtual Worlds
Streaming hierarchical video segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Shape priors extraction and application for geodesic distance transforms in images and videos
Pattern Recognition Letters
Integrating tracking with fine object segmentation
Image and Vision Computing
Random walks in directed hypergraphs and application to semi-supervised image segmentation
Computer Vision and Image Understanding
Smoke Detection in Video: An Image Separation Approach
International Journal of Computer Vision
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An interactive framework for soft segmentation and matting of natural images and videos is presented in this paper. The proposed technique is based on the optimal, linear time, computation of weighted geodesic distances to user-provided scribbles, from which the whole data is automatically segmented. The weights are based on spatial and/or temporal gradients, considering the statistics of the pixels scribbled by the user, without explicit optical flow or any advanced and often computationally expensive feature detectors. These could be naturally added to the proposed framework as well if desired, in the form of weights in the geodesic distances. An automatic localized refinement step follows this fast segmentation in order to further improve the results and accurately compute the corresponding matte function. Additional constraints into the distance definition permit to efficiently handle occlusions such as people or objects crossing each other in a video sequence. The presentation of the framework is complemented with numerous and diverse examples, including extraction of moving foreground from dynamic background in video, natural and 3D medical images, and comparisons with the recent literature.