IEEE Transactions on Pattern Analysis and Machine Intelligence
Adapting optical-flow to measure object motion in reflectance and X-ray image sequences
Proc. of the ACM SIGGRAPH/SIGART interdisciplinary workshop on Motion: representation and perception
Scene Segmentation from Visual Motion Using Global Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Flow Segmentation and Estimation by Constraint Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analog hardware for detecting discontinuities in early vision
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
Optical flow estimation: advances and comparisons
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Compact Representations of Videos Through Dominant and Multiple Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
The Frequency Structure of One-Dimensional Occluding Image Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Measurement of Image Velocity
Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Optic flow calculation using robust statistics
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)
A model of figure-ground segregation from kinetic occlusion
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
MAP-Based Stochastic Diffusion for Stereo Matching and Line Fields Estimation
International Journal of Computer Vision
Guest Editorial: Computational Vision at Brown
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian inference of visual motion boundaries
Exploring artificial intelligence in the new millennium
Multiple motion analysis: in spatial or in spectral domain?
Computer Vision and Image Understanding
Layered Motion Segmentation and Depth Ordering by Tracking Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate optical flow computation under non-uniform brightness variations
Computer Vision and Image Understanding
Piecewise-Smooth Dense Optical Flow via Level Sets
International Journal of Computer Vision
A Roadmap to the Integration of Early Visual Modules
International Journal of Computer Vision
Learning Layered Motion Segmentations of Video
International Journal of Computer Vision
Computing Stable Skeletons with Particle Filters
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
A Geometric Framework and a New Criterion in Optical Flow Modeling
Journal of Mathematical Imaging and Vision
Contour Grouping with Partial Shape Similarity
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Occlusion Boundaries from Motion: Low-Level Detection and Mid-Level Reasoning
International Journal of Computer Vision
Contour Grouping Based on Contour-Skeleton Duality
International Journal of Computer Vision
Local detection of occlusion boundaries in video
Image and Vision Computing
Accurate optical flow computation under non-uniform brightness variations
Computer Vision and Image Understanding
Estimation of distributed hybrid systems Using particle filtering methods
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Local occlusion detection under deformations using topological invariants
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Recovering Occlusion Boundaries from an Image
International Journal of Computer Vision
Motion segmentation using an occlusion detector
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Detecting spatiotemporal structure boundaries: beyond motion discontinuities
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Intrackability: Characterizing Video Statistics and Pursuing Video Representations
International Journal of Computer Vision
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We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are represented using a non-linear generative model that explicitly encodes the orientation of the boundary, the velocities on either side, the motion of the occluding edge over time, and the appearance/disappearance of pixels at the boundary. We represent the posterior probability distribution over the model parameters given the image data using discrete samples. This distribution is propagated over time using a particle filtering algorithm. To efficiently represent such a high-dimensional space we initialize samples using the responses of a low-level motion discontinuity detector. The formulation and computational model provide a general probabilistic framework for motion estimation with multiple, non-linear, models.