Michael Werman
The Hebrew University of Jerusalem
Jerusalem 91904
Israel
e-mail: [email protected]
phone: +972-2-54-94541
fax: +972-2-54-94541
office: B506, Rothberg Building, Givat Ram
Campus
Research
Interests
- Computer Vision
- Geometric Algorithms
- Statistical Algorithms
Prospective Graduate Students / PostDocs
Selected publications on-line
Cana
Cameroon
Selected
publications on-line
Epipolar Geometry Based On Line
Similarity,
G. Ben-Artzi, T. Halperin, M. Werman, and S. Peleg, ICPR'16, 2016.
Fundamental Matrices from Moving Objects Using Line Motion
Barcodes,
Y. Kasten, G. Ben-Artzi, S. Peleg, and M. Werman, ECCV'16, �2016.
Camera Calibration from Dynamic Silhouettes Using Motion
Barcodes,
G. Ben-Artzi, Y. Kasten, S. Peleg, and M. Werman, CVPR'16, 2016.
Complex-Valued
Hough Transforms for Circles.
Marcelo Cicconet, Davi Geiger and� Michael Werman.� ICIP, 2015.
Event
Retrieval Using Motion Barcodes.
G. Ben-Artzi, M. Werman and S. Peleg. ICIP, 2015.
Extracting Scar
and Ridge Features from 3D-scanned Lithic Artifacts .
E. Richardson, L. Grosman, U. Smilansky and� M. Werman. Archaeology in the Digital Era, p. 83, 2014.
Efficient classification using the Euler characteristic.
E. Richardson and M. Werman. Pattern Recognition Letters, 2014. Code
Scene
Geometry from Moving Objects .
E. Richardson and S. Peleg and M. Werman. AVSS, 2014
M. Cicconet and K. Gunsalus and D. Geiger and M. Werman. ICIP, 2014
Optical
Flow for non Lambertian surfaces by cancelling
illuminant chromaticity .
C. Arora and M. Werman. ICIP, 2014
Shape
Statistics for Cell Division Detection in Time-Lapse Videos of Early Mouse Embryo .
M. Cicconet and K. Gunsalus and D. Geiger and M. Werman. ICIP, 2014
Mirror
Symmetry Histograms for Capturing Geometric Properties in Images
.
M. Cicconet and D. Geiger and K. Gunsalus nd M. Werman. CVPR, 2014
Automatic Recovery of the Atmospheric Light in Hazy Images.
M. Sulami and I. Geltzer and R. Fattal� and M. Werman. ICCP, 2013
Illuminant
Chromaticity from Image Sequences.
V. Prinet and D. Lischinski and M. Werman. International Conference on Computer Vision (ICCV), 2013
Specular
Highlight Enhancement from Video Sequences.
V. Prinet and M. Werman and D. Lischinski. ICIP, 2013
Asymmetric
Correlation: a Noise Robust Similarity Measure for Template Matching.
E. Elboher and M. Werman. IEEE Transactions on Image Processing (TIP), 2013
The Generalized Laplacian Distance and
its Applications for Visual Matching.
E. Elboher, M. Werman, and Y. Hel-Or. CVPR 2013.
The Pairwise Piecewise-Linear Embedding
for Efficient Non-Linear Classification.
Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman. ICML 2013.
Efficient and
Accurate Gaussian Image Filtering Using Running Sums.
E. Elboher and M. Werman. SoCPar 2012, Brunei.
Improving Perceptual Color Difference using Basic Color Terms.
Ofir Pele and Michael Werman. arXiv 2012.
Content-Aware Automatic Photo Enhancement.
L. Kaufman, D. Lischinski, and M. Werman. COMPUTER GRAPHICS Forum 2012.
Extracting Scar and Ridge Features from 3D-scanned Lithic Artifacts.
E. Richardson, L. Grossman, U. Smilansky, and M. Werman. CAA 2012.
D. Honigstein, J. Weinroth, M. Werman, and A. Lewis. ACS Nano, 2012, 6 (1), pp 220�226. DOI: 10.1021/nn203427z
Probabilistic Approach to Pattern Matching in the Continuous
Domain.
D. Keren, M. Werman, J. Feinberg. PAMI 2012.
Cosine Integral Images
for Fast Spatial and Range Filtering.
E. Elboher and M. Werman. ICIP 2011, Brussels.
A curvelet-based patient-specific prior for accurate
multi-modal brain image rigid registration.
M. Freiman,� M. Werman and L. Joskowicz. Medical Image Analysis Volume 15, Issue 1, February 2011, Pages 125-132.
The Quadratic-Chi Histogram Distance Family. O. Pele and M. Werman. ECCV 2010. Code��
Robust Head Pose Estimation by Fusing Time-of-Flight Depth and Color. A. Bleiweiss and M. Werman. MMSP 2010.
Recovering Color and Details of Clipped Image Regions.
E. Elboher and M. Werman. CGVCVIP 2010.� Project page
Robust Real Fusing Time-of-Flight Depth and Color for Real-Time
Segmentation and Tracking.
A. Bleiweiss and M. Werman. Dynamic 3D Imaging 2009.
Fast and Robust Earth Mover's Distances.
O. Pele and M. Werman. ICCV 2009. Code�
Applying Two-Pixel Features to Face Detection. �
I. Nissenboim, D. Keren, and M. Werman.
IEEE International Conference on Signal Image Technology and Internet Based
Systems, 2008.
A Linear Time
Histogram Metric for Improved SIFT Matchings. �
O. Pele and M. Werman. ECCV 2008. Code
Robust
Real Time Pattern Matching using Bayesian Sequential Hypothesis Testing
O. Pele and M. Werman. PAMI, 2008. Code
Accelerating
Pattern Matching or How Much Can You Slide?
O. Pele and M. Werman. ACCV, 2007. Code
Vertical Parallax from Moving Shadows.
Y. Caspi and M. Werman. CVPR, 2006.
The Bottleneck
Geodesic: Computing Pixel Affinity.
I. Omer and M. Werman. CVPR, 2006.
E. Begelfor and M. Werman. CVPR, 2006.
Image Specific Feature Similarities.
I. Omer and M. Werman. ECCV, 2006.
The World is not
(always) Flat or Learning Curved Manifolds.
E. Begelfor and M. Werman. HUJI-CSE-LTR-2006-191� PAMI,� 2006.
How to Put Probabilities on Homographies.
E. Begelfor and M. Werman. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 27, NO. 10, OCTOBER 2005.
On
using priors in affine matching.
V. Govindu and M. Werman. Image and Vision Computing, V 22, 14, Dec 2004, Pages 1157-1164.
Using Natural Image Properties as Demosaicing
Hints.
I. Omer and M. Werman. ICCV 2004.
Color Lines:
Image Specific Color Representation.
I. Omer and M. Werman. CVPR 2004.
S. Starik and� M. Werman Texture03. rain videos�
Unsupervised
Clustering of Images using their Joint Segmentation
Y. Seldin, S. Starik� and� M. Werman SCTV03.�
N. Levi and� M. Werman �CVPR 2003, II:599-606.��
Study
of Mutual Information in Perceptual Coding with Application for Low Bit-Rate
Compression.
A. Ben-Shalom, S. Dubnov and M. Werman �Fourth International Symposium on Independent Component Analysis and Blind Source Separation. ICA 2003
Improved
Low bit-rate audio compression using reduced rank ICA instead of psychoacoustic
modeling.
A. Ben-Shalom, S. Dubnov and M. Werman �IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP2003
M. Werman. WSCG 2003, Feb 2003.���
On
using Priors in Affine Matching
V. Govindu, and M. Werman. Indian Conference on Computer Vision, Graphics and Image Processing, 2002.��� ����
Gradient
domain high dynamic range compression
R. Fattal, D. Lischinski, and M. Werman. ACM Transactions on Graphics (Proc. ACM SIGGRAPH 2002), July 2002.
On All Points Considered: A Maximum
Likelihood Method for Motion Recovery
Daniel Keren and Ilan Shimshoni and� Liran Goshen and� Michael Werman, Theoretical Foundations of Computer Vision, Springer LNCS series 2616, 72-85, (2003).���
Parameter Estimates for a Pencil of Lines:
Bounds and Estimators
G. Speyer and M. Werman, ECCV, 2002.��
A
Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data
M. Werman and D. Keren, PAMI, 23, 5, 528-534, 2001.���
Texture mixing and
texture movie synthesis using statistical learning
Z. Bar-Joseph, R. El-Yaniv, D. Lischinski, and� M. Werman, IEEE Transactions on Visualization and Computer Graphics, 7(2), 2001, pp. 120-135��
Y. Gdalyahu, D. Weinshall and M. Werman, IEEE Trans. on Pattern Analysis and Machine Intelligence, 23(10):1053-1074, 2001. ���
Structure from
Motion using Points, Lines, and Intensities
J. Oliensis and� M. Werman, CVPR 2000, II:599-606.���
Model Based Pose
Estimator using Linear Programming
M. Ben-Ezra, S. Peleg and M. Werman�� ECCV2000
Real-Time Motion
Analysis with Linear Programming,
M. Ben-Ezra, S. Peleg, and M. Werman, Computer Vision and Image Understanding, Vol. 78, No. 1, Apr 2000, pp. 32-52.��
A Full
Bayesian Approach to Curve and Surface Reconstruction
D. Keren and M. Werman, JMIV, 11, 27-43, 1999.���
Robot Localization
using Uncalibrated Camera Invariants
M. Werman, S. Banerjee, S. Dutta Roy and M. Qiu. IEEE CVPR'99, II:353-359, 1999.��
Trajectory
Triangulation over Conic Sections
A. Shashua, S. Avidan and M. Werman, International Conference on Computer Vision (ICCV)� 330-336, Sep., 1999.� ����
Minimal Decomposition of
Model-Based Invariants
Weinshall and M. Werman,
JMIV 10(1):77-87, 1999.� ����
A method
for on-line clustering of non-stationary data
I.D. Guedalia, M. London and M Werman, �Neural Computation 11:551-571,� 1999.
Real-Time
Object Tracking from a Moving Video Camera: A Software Approach on a PC
Y. Rosenberg and M. Werman, IEEE Workshop on Applications of Comuter Vision, Princeton, Oct 1998, pp. 238-239.� ����
Representing local
motion as a probability distribution matrix applied to object tracking
Y. Rosenberg and M. Werman, �CVPR, 1997, pp. 654--659.� ����
A General Filter for
Measurements with any Probability Distribution
Y. Rosenberg and M. Werman, CVPR, 1997, pp. 106--111.� ����
On View
Likelihood and Stability
Weinshall and M. Werman, IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(2):97-108, 1997.���
Duality Of Multi-Point And Multi-Frame Geometry: Fundamental Shape
Matrices And Tensors
Weinshall, M. Werman and A. Shashua, �ECCV-96, II:217-227,� Cambridge, April 1996.
Similarity
and Affine Invariant Distance Between Point Sets
M. Werman and D. Weinshall, �PAMI,� 17(8), pp. 810-814, August 1995.
The Study of
3D-from-2D using Elimination
M. Werman and A. Shashua, Int. Conf. Computer Vision, Boston, June 1995, 473-479.
Fitting a
Second Degree Curve if Both Coordinates are Subject to
Error
M. Werman and Z. Geyzel, PAMI, 17,207--211, 1995.
Trilinearity of Three Perspective Views and its Associated
Tensor
A. Shashua and M. Werman, Int. Conf. Computer Vision, Boston, June 1995, 920-925.
Linear Time
Euclidean Distance Transform and Voronoi Diagram
Algorithms
H. Breu and J. Gil and D. Kirkpatrck and M. Werman, PAMI, 17, 529--533, 1995.
Pose
Estimation by Fusing Noisy Data of Different Dimensions
Y. Hel-Or and M. Werman, PAMI Vol 17, No. 2, Feb 1995.
Localization
of Primitives Using Adaptive Projections
Y. Hel-Or and M. Werman, Journal of Intelligent and Robotic Systems Vol 11, 161-174 1994.
Highlight
and Reflection Independent Multiresolution Textures
from Image Sequences
E. Ofek, E. Shilat, A. Rappoport, and M. Werman, IEEE Computer Graphics and Applications, 1994, 17, 18-29.
Model Based
Pose Estimation of Articulated and Constrained Objects
Y. Hel-Or, M. Werman, ECCV-94, Stockholm, 267-273, May 1994.
Stability and
Likelihood of Views of Three Dimensional Objects
Weinshall, M. Werman and N. Tishby, ����ECCV, Stockholm, May 1994, pp. 24--35.
Constraint-Fusion
for Interpretation of Articulated Objects
Y. Hel-Or, M. Werman, �CVPR-94, Seattle, June 1994, pp. 39--45.
Similarity and Affine
Distance Between Point Sets
M. Werman, D. Weinshall, ��12-ICPR, Jerusalem,� Vol I, pp. 723-725, October 1994.
E. M. Arkin and K. Kedem and J. S. B. Mitchell and J. Sprinzak and M. Werman, �ORSA Journal on Computing, special issue on computational geometry, 27-52, 1992.
Probabilistic
Analysis of Regularization
D. Keren and M. Werman, �PAMI, 15, 983-1001, 1993.���
Computing
2D Min, Max and Median Filters
Y. Gil and� M. Werman, �PAMI, 15, 504-507, 1993.
Finding the Repeated
Median Regression Line
A. Stein and M. Werman, �3'rd Symposium on Discrete Algorithms, 409--413, 1992.
Robust
Statistics in Shape Fitting
A. Stein and M. Werman, Computer Vision and Pattern Recognition, 540-546, 1992.
Segmenting
and Compressing by Minimal Length Encoding
D. Keren
and R. Marcus and M. Werman, 10'th
International Conference on Pattern Recognition 681--683, 1990.
A Unified Approach
to the Change of Resolution: Space and Gray-Level
S. Peleg and M. Werman and H. Rom, ���PAMI 11, 739-742
P. Lemke and M. Werman, Tech Report, 1988.
Halftoning as Optimal Quantization
S. Peleg and M. Werman, 8th ICPR, 1986, pp. 1114-1116.
Bipartite
graph matching for points on a line or a circle
M. Werman, S. Peleg, R. Melter, and T.Y. Kong, Journal of Algorithms, Vol. 7, 1986, pp. 277-284.
A
distance metric for multidimensional histograms
M. Werman, S. Peleg, and A. Rosenfeld, CVGIP, Vol. 32, Dec. 1985, pp. 328-336.
Min max
operators in texture analysis
M. Werman and S. Peleg, Trans. on PAMI, Vol 7, Nov. 1985, pp. 730-733.