An Integrated Bayesian Approach to Layer Extraction from Image Sequences
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
The MPEG-4 Book
Video matting of complex scenes
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Cooperative Robust Estimation Using Layers of Support
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Layered Motion Representation with Occlusion and Compact Spatial Support
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Bayesian Estimation of Layers from Multiple Images
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Layered Approach to Stereo Reconstruction
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Background Layer Model for Object Tracking Through Occlusion
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
Probabilistic Fusion of Stereo with Color and Contrast for Bilayer Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Framework for Simultaneous Matting and 3D Reconstruction
3DIM '07 Proceedings of the Sixth International Conference on 3-D Digital Imaging and Modeling
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts
International Journal of Computer Vision
Joint 3D-reconstruction and background separation in multiple views using graph cuts
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Representing moving images with layers
IEEE Transactions on Image Processing
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We present an algorithm for the layered segmentation of video data in multiple views. The approach is based on computing the parameters of a layered representation of the scene in which each layer is modelled by its motion, appearance and occupancy, where occupancy describes, probabilistically, the layer's spatial extent and not simply its segmentation in a particular view. The problem is formulated as the MAP estimation of all layer parameters conditioned on those at the previous time step; i.e., a sequential estimation problem that is equivalent to tracking multiple objects in a given number views. Expectation-Maximisation is used to establish layer posterior probabilities for both occupancy and visibility, which are represented distinctly. Evidence from areas in each view which are described poorly under the model is used to propose new layers automatically. Since these potential new layers often occur at the fringes of images, the algorithm is able to segment and track these in a single view until such time as a suitable candidate match is discovered in the other views. The algorithm is shown to be very effective at segmenting and tracking non-rigid objects and can cope with extreme occlusion. We demonstrate an application of this representation to dynamic novel view synthesis.