Scene Segmentation from Visual Motion Using Global Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Prior Learning and Gibbs Reaction-Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Reliable Estimation of Dense Optical Flow Fields with Large Displacements
International Journal of Computer Vision
The statistics of optical flow
Computer Vision and Image Understanding
Probability Models for Clutter in Natural Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
Occlusion Models for Natural Images: A Statistical Study of a Scale-Invariant Dead Leaves Model
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
Hierarchical Estimation and Segmentation of Dense Motion Fields
International Journal of Computer Vision
On Advances in Statistical Modeling of Natural Images
Journal of Mathematical Imaging and Vision
Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Training products of experts by minimizing contrastive divergence
Neural Computation
Contextual Priming for Object Detection
International Journal of Computer Vision
Determination of Optical Flow and its Discontinuities using Non-Linear Diffusion
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Bayesian inference of visual motion boundaries
Exploring artificial intelligence in the new millennium
Energy-based models for sparse overcomplete representations
The Journal of Machine Learning Research
A column pre-ordering strategy for the unsymmetric-pattern multifrontal method
ACM Transactions on Mathematical Software (TOMS)
The world from a cat’s perspective – statistics of natural videos
Biological Cybernetics
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
On the Spatial Statistics of Optical Flow
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
A General Framework and New Alignment Criterion for Dense Optical Flow
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
On the equivalence of variational and statistical differential motion estimation
SSIAI '06 Proceedings of the 2006 IEEE Southwest Symposium on Image Analysis and Interpretation
Learning static object segmentation from motion segmentation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
A comparative study of energy minimization methods for markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Surface Visibility Probabilities in 3D Cluttered Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Measuring the Similarity of Vector Fields Using Global Distributions
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
International Journal of Computer Vision
Optimal extended optical flow subject to a statistical constraint
Journal of Computational and Applied Mathematics
Estimation and analysis of urban traffic flow
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Occlusion boundary detection using pseudo-depth
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Dynamic color flow: a motion-adaptive color model for object segmentation in video
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Journal of Visual Communication and Image Representation
Spatio-temporal optical flow statistics (STOFS) for activity classification
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
Over-Parameterized optical flow using a stereoscopic constraint
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Variation in the local motion statistics of real-life optic flow scenes
Neural Computation
Efficient nonlocal regularization for optical flow
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
A naturalistic open source movie for optical flow evaluation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Computer Vision and Image Understanding
A Survey of Optical Flow Techniques for Robotics Navigation Applications
Journal of Intelligent and Robotic Systems
Event classification for vehicle navigation system by regional optical flow analysis
Machine Vision and Applications
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We present an analysis of the spatial and temporal statistics of "natural" optical flow fields and a novel flow algorithm that exploits their spatial statistics. Training flow fields are constructed using range images of natural scenes and 3D camera motions recovered from hand-held and car-mounted video sequences. A detailed analysis of optical flow statistics in natural scenes is presented and machine learning methods are developed to learn a Markov random field model of optical flow. The prior probability of a flow field is formulated as a Field-of-Experts model that captures the spatial statistics in overlapping patches and is trained using contrastive divergence. This new optical flow prior is compared with previous robust priors and is incorporated into a recent, accurate algorithm for dense optical flow computation. Experiments with natural and synthetic sequences illustrate how the learned optical flow prior quantitatively improves flow accuracy and how it captures the rich spatial structure found in natural scene motion.