Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video matting of complex scenes
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Match Propogation for Image-Based Modeling and Rendering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cooperative Robust Estimation Using Layers of Support
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation by Multiscale Aggregation of Filter Responses and Shape Elements
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
ACM SIGGRAPH 2004 Papers
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
Accurate Motion Layer Segmentation and Matting
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ACM SIGGRAPH 2005 Papers
Segmentation by Level Sets and Symmetry
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
What Is a Good Image Segment? A Unified Approach to Segment Extraction
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Video SnapCut: robust video object cutout using localized classifiers
ACM SIGGRAPH 2009 papers
Refilming with Depth-Inferred Videos
IEEE Transactions on Visualization and Computer Graphics
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
Motion layer extraction in the presence of occlusion using graph cut
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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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The problem of accurate video layer decomposition is of vital importance in computer vision. Previous methods mainly focus on the foreground extraction. In this paper, we present a user-assisted framework to decompose videos and extract all layers, which is built on the depth information and over-segmented patches. The task is split into two stages: i) the clustering of over-segmented patches; ii) the propagation of layers along the video. Correspondingly, this paper has two contributions: i) a video decomposition method based on greedy over-segmented patches merging; ii) a layer propagation method via iteratively updating color Gaussian Mixture Models(GMM). We test this algorithm on real videos and verify that it outperforms state-of-the-art methods.