Parallel and Deterministic Algorithms from MRFs: Surface Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
International Journal of Computer Vision
Reliable and Efficient Computation of Optical Flow
International Journal of Computer Vision
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Empirical Bayesian Motion Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gauss-Markov Measure Field Models for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing: Concepts, Algorithms, and Scientific Applications
Digital Image Processing: Concepts, Algorithms, and Scientific Applications
Measurement of Image Velocity
Smoothness in Layers: Motion segmentation using nonparametric mixture estimation.
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
The recovery of a near optimal layer representation for an entire image sequence
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Motion Segmentation and Tracking Using Normalized Cuts
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
A variational framework for image segmentation combining motion estimation and shape regularization
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Multiple motion segmentation with level sets
IEEE Transactions on Image Processing
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
A method of motion segmentation based on region shrinking
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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We present an MPM-MAP application for the efficient estimation of piecewise parametric models for motion segmentation. This algorithm permits the simultaneous estimation of: the number of models, the parameters for each model and the regions where each model is applicable. It is based on Bayesian estimation theory, and is theoretically justified by the use of a specific cost function whose expected value decreases at every iteration and by a new model for the posterior marginal distributions which is amenable to the use of fast computational methods. We compare the performance of this method with the most similar segmentation algorithm, the well known Expectation-Maximization algorithm. We present a comparison of the performance of both algorithms using synthetic and real image sequences.