Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
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
ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2005 Papers
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
Bilayer Segmentation of Live Video
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Dynamical Statistical Shape Priors for Level Set-Based Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monocular Video Foreground/Background Segmentation by Tracking Spatial-Color Gaussian Mixture Models
WMVC '07 Proceedings of the IEEE Workshop on Motion and Video Computing
Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation
International Journal of Computer Vision
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts
International Journal of Computer Vision
Image Segmentation by Branch-and-Mincut
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Interactive Image Segmentation via Adaptive Weighted Distances
IEEE Transactions on Image Processing
Spatio-temporal video segmentation using a joint similarity measure
IEEE Transactions on Circuits and Systems for Video Technology
Combining shape prior and statistical features for active contour segmentation
IEEE Transactions on Circuits and Systems for Video Technology
Recognition of dynamic visual images based on group transformations
Pattern Recognition and Image Analysis
Ultrasound kidney segmentation with a global prior shape
Journal of Visual Communication and Image Representation
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Segmenting semantic objects of interest from video has long been an active research topic, with a wide range of potential applications. In this paper, we present a bilayer video segmentation method robust to abrupt motion and change in appearance for both the foreground and background. Specifically, based on a few manually segmented keyframes, the proposed method propagates the global shape of the foreground as priors to adjacent frames by applying branch-and-mincut [1], which jointly estimates what is optimal among a set of shapes along with its pose and the corresponding segmentation in the current image. Based on this preliminary segmentation we determine two types of local regions likely to have erroneous results, and apply a probabilistic framework where shape and appearance cues are adaptively emphasized for local refinement. With each successive frame segmentation, the set of shapes applied as priors are incrementally updated. Experimental results support the robustness of the proposed method for obstacles such as background clutter, motion, and appearance changes, from only a small number of user segmented keyframes.