Video Segmentation by MAP Labeling of Watershed Segments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Smoothness in Layers: Motion segmentation using nonparametric mixture estimation.
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Robust Subspace Approach to Layer Extraction
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multi-View Subspace Constraints on Homographies
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Motion Segmentation and Tracking Using Normalized Cuts
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Two-Frame Wide Baseline Matching
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Background Layer Model for Object Tracking Through Occlusion
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Computing Geodesics and Minimal Surfaces via Graph Cuts
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Adaptive Region-Based Video Registration
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Motion Layer Extraction in the Presence of Occlusion Using Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion
International Journal of Computer Vision
Video object segmentation by motion-based sequential feature clustering
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Image-Based Modeling by Joint Segmentation
International Journal of Computer Vision
Dynamic Graph Cuts for Efficient Inference in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Foreground Segmentation via Segments Tracking
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Robust subspace clustering by combined use of kNND metric and SVD algorithm
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Interactive video layer decomposition and matting
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
A novel spatio-temporal approach to handle occlusions in vehicle tracking
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Extraction of layers of similar motion through combinatorial techniques
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
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Extracting layers from video is very important for video representation, analysis, compression, and recognition. Assuming that a scene can be approximately described by multiple planar regions, this paper describes a robust novel approach to automatically extract a set of affine transformations induced by these regions, and accurately segment the scene into several motion layers. First, a number of seed regions are determined by using two frame correspondences. Then the seed regions are expanded and refined using the level set representation and employing graph cut method. Next, these initial regions are merged into several initial layers according to the motion similarity. Third, after exploiting the occlusion order constraint on multiple frames the robust layer extraction is obtained by graph cut algorithm, and the occlusions between the overlapping layers are explicitly determined. Several examples are demonstrated in the experiments to show that our approach is effective and robust.