Visual reconstruction
Bayesian modeling of uncertainty in low-level vision
International Journal of Computer Vision
A Three-Frame Algorithm for Estimating Two-Component Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric invariance in computer vision
Geometric invariance in computer vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A Bayesian approach to binocular stereopsis
International Journal of Computer Vision
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
Algorithmic issues in modeling motion
ACM Computing Surveys (CSUR)
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Factorial Markov Random Fields
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A Probabilistic Theory of Occupancy and Emptiness
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Automatic acquisition and initialization of articulated models
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
Extracting View-Dependent Depth Maps from a Collection of Images
International Journal of Computer Vision - Special Issue on Research at Microsoft Corporation
LAMP: 3D layered, adaptive-resolution, and multi-perspective panorama—a new scene representation
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Generalized Principal Component Analysis (GPCA)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion segmentation using inertial sensors
Proceedings of the 2006 ACM international conference on Virtual reality continuum and its applications
Object Level Grouping for Video Shots
International Journal of Computer Vision
Two-View Multibody Structure from Motion
International Journal of Computer Vision
Probabilistic Fusion of Stereo with Color and Contrast for Bilayer Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation and Estimation
Journal of Mathematical Imaging and 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
Adaptive probabilistic tracking embedded in smart cameras for distributed surveillance in a 3D model
EURASIP Journal on Embedded Systems
Bayesian object extraction from uncalibrated image pairs
Image Communication
Learning Layered Motion Segmentations of Video
International Journal of Computer Vision
Dense and Deformable Motion Segmentation for Wide Baseline Images
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Bilayer representation for three dimensional visual communication
Journal of Visual Communication and Image Representation
Taxonomy of directing semantics for film shot classification
IEEE Transactions on Circuits and Systems for Video Technology
Stereovision-based 3D planar surface estimation for wall-climbing robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Multiview segmentation and tracking of dynamic occluding layers
Image and Vision Computing
Bayesian approaches to motion-based image and video segmentation
IWCM'04 Proceedings of the 1st international conference on Complex motion
3D motion segmentation from straight-line optical flow
MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
Learning spatio-temporal dependency of local patches for complex motion segmentation
Computer Vision and Image Understanding
The space of multibody fundamental matrices: rank, geometry and projection
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Direct segmentation of multiple 2-D motion models of different types
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Shortest path based planar graph cuts for bi-layer segmentation of binocular stereo video
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume part II
A Probabilistic Contour Observer for Online Visual Tracking
SIAM Journal on Imaging Sciences
Background updating for visual surveillance
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
A bottom up algebraic approach to motion segmentation
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Dense optic flow with a bayesian occlusion model
SCVMA'04 Proceedings of the First international conference on Spatial Coherence for Visual Motion Analysis
Bilayer segmentation augmented with future evidence
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
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This paper describes a Bayesian approach for modeling 3D scenes as a collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. In contrast to much of the previous work on layer-based motion modeling, which computes layered descriptions of 2D image motion, our work leads to a 3D description of the scene. There are two contributions within the paper. The first is to formulate the prior assumptions about the layers and scene within a Bayesian decision making framework which is used to automatically determine the number of layers and the assignment of individual pixels to layers. The second is algorithmic. In order to achieve the optimization, a Bayesian version of RANSAC is developed with which to initialize the segmentation. Then, a generalized expectation maximization method is used to find the MAP solution.