Werman, Michael - School of Computer Science and Engineering, Hebrew University of Jerusalem

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Werman, Michael - School of Computer Science and Engineering, Hebrew University of Jerusalem

How to Put Probabilities on Homographies Evgeni Begelfor and Michael Werman
Accelerating Pattern Matching How Much Can You Slide?
Real-Time Object Tracking from a Moving Video Camera: A Software Approach on a PC
A general filter for measurements with any probability distribution Yoav Rosenberg Michael Werman
Robust Real Time Pattern Matching using Bayesian Sequential Hypothesis Testing
The Quadratic-Chi Histogram Distance Family Ofir Pele and Michael Werman
RECOVERING COLOR AND DETAILS OF CLIPPED IMAGE REGIONS
Fast and Robust Earth Mover's Distances The Hebrew University of Jerusalem
Vertical Parallax from Moving Shadows Yaron Caspi
Affine invariance revisited Evgeni Begelfor Michael Werman
Color Lines: Image Specific Color Representation. Ido Omer and Michael Werman
Simulation of Rain in Videos Sonia Starik Michael Werman
On Using Priors in Affine Matching Venu Govindu Michael Werman
Journal of Mathematical Imaging and Vision 11, 2743 (1999) c 1999 Kluwer Academic Publishers. Manufactured in The Netherlands.
Short Papers___________________________________________________________________________________________________ A Bayesian Method for Fitting Parametric and
Journal of Intelligent and Robotic Systems 11: 161-174, 1994. 161 O 1994 Kluwer Academic Publishers. Printed in the Netherlands.
On using priors in affine matching Venu Madhav Govindua,*, Michael Wermanb
STUDY OF MUTUAL INFORMATION IN PERCEPTUAL CODING WITH APPLICATION FOR LOW BIT-RATE COMPRESSION
The Bottleneck Geodesic: Computing Pixel Affinity Ido Omer Michael Werman
Real-Time Motion Analysis with Linear-Programming1 Moshe Ben-Ezra and Shmuel Peleg and Michael Werman
A Linear Time Histogram Metric for Improved SIFT Matching
Fast Convolution Michael Werman
Learning Curved Manifolds The World is not always Flat
Texture Mixing and Texture Movie Synthesis using Statistical Learning
Unsupervised Clustering of Images using their Joint Segmentation
Image Specific Feature Similarities Ido Omer and Michael Werman
Representing local motion as a probability distribution matrix and object tracking
IMPROVED LOW BIT-RATE AUDIO COMPRESSION USING REDUCED RANK ICA INSTEAD OF PSYCHOACOUSTIC MODELING
The Viewing Graph Noam Levi Michael Werman
Applying Two-Pixel Features to Face Detection Ido Nissenboim
A curvelet-based patient-specific prior for accurate multi-modal brain image rigid registration
COSINE INTEGRAL IMAGES FOR FAST SPATIAL AND RANGE FILTERING Elhanan Elboher and Michael Werman
A Probabilistic Approach to Pattern Matching in the Continuous Domain