Michal Irani
Professor.
Dept. of
Computer Science and Applied Math
(Ziskind building,
room 225)
The Weizmann
Institute of Science
Rehovot, 76100 ISRAEL
E-mail: michal.irani
weizmann.ac.il
Phone:
+972-8-9344297
My research area is computer vision and video
information analysis. In the past few years it has focused on two main
themes:
1. Space-Time Analysis of Video:
Although space and time are very different in nature,
they are closely interrelated. This leads to inherent visual trade-offs between
time and space. This is also what makes video much more than just a plain
collection of images of the same scene taken from different view-points.
Therefore, in contrast to the traditional way of analyzing video on a
frame-by-frame basis, my work over the past few years has focused on analyzing
simultaneously all available data in entire space-time volumes. I have
shown that such a space-time approach is essential in order to perform tasks
that are very difficult and often impossible to perform otherwise, when
only “slices” of this information are used (such as discrete image frames or
discrete feature points). The space-time approach gives rise to new powerful
ways of analyzing and exploiting recorded visual information from single and
multiple visual sources.
My research work in this area is aimed toward: (a) developing theories and tools for
analysis and interpretation of space-time visual information, (b) developing methods to exploit this rich
visual information for useful real-world applications, and (c) develop new and improved visual
capabilities that exceed optical bounds of today’s visual sensors (including
the human eye).
2. Visual Inference by Composition:
I have recently begun developing an
"Inference-by-Composition" approach, which gives rise to analysis and
prediction of complex visual information (both in images and in video data)
without resorting to any pre-defined parametric models, nor requiring an
exhaustive set of prior visual examples (which are often relied upon). Visual
"pieces of evidence" from a small number of available visual examples
are composed and integrated into new global visual configurations that were
never seen before. This allows to make inferences
about the likelihood of a combinatorially large set
of complex scenes and events that were never observed. This "Inference by
Composition" approach opens the door to analysis and prediction of very
complex static and dynamic information, which could not have been previously
handled. Moreover, the applicability of this approach extends beyond the field
of Computer Vision to multiple disciplines and research areas. I am currently
working towards developing it into a general approach to the representation and
analysis of visual as well as non-visual digital data.
More details can be found in my papers below and in
their corresponding demo webpages.
Publications:
- T. Michaeli
and M. Irani, Blind Deblurring
Using Internal Patch Recurrence. European
Conference on Computer Vision (ECCV), September 2014. *See webpage with results and code.
- A. Faktor
and M. Irani, Video
Segmentation by Non-Local Consensus Voting. British
Machine Vision Conference (BMVC), September 2014. *See webpage with results and code.
- A. Faktor
and M. Irani, “Clustering
by Composition” – Unsupervised Discovery of Image Categories. IEEE Transactions on Pattern Analysis and
Machine Intelligence (PAMI), 36(6):
1092-1106, June 2014. *See webpage with results and code.
(A shorter version of
this paper appeared in ECCV 2012.)
- T. Michaeli
and M. Irani, Nonparametric
Blind Super-Resolution. International
Conference on Computer Vision (ICCV), October 2013. *See webpage with examples and results.
- A. Faktor
and M. Irani, Co-Segmentation
by Composition. International
Conference on Computer Vision (ICCV), October 2013. *See webpage with results and code.
- M. Zontak, I.
Mosseri and M. Irani, Separating
Signal from Noise using Patch Recurrence Across Scales IEEE
Conference on Computer Vision and Pattern Recognition (CVPR), June
2013. *See
webpage with examples and results .
- I. Mosseri, M. Zontak and
M. Irani, Combining the Power of Internal and External Denoising IEEE
International Conference on Computational Photography (ICCP), April 2013.
- A. Faktor
and M. Irani, “Clustering
by Composition” – Unsupervised Discovery of Image Categories. European
Conference on Computer Vision (ECCV), October 2012. *See webpage with results, proofs,
and code.
- M. Zontak and M. Irani, Internal
Statistics of a Single Natural Image. IEEE
Conference on Computer Vision and Pattern
Recognition (CVPR), June 2011. *See webpage with examples and results .
- O. Shahar, A. Faktor and
M. Irani, Space-Time
Super-Resolution from a Single Video. IEEE
Conference on Computer Vision and Pattern
Recognition (CVPR), June 2011. *See webpage with example sequences and results .
- S. Bagon, O. Brostovsky, M. Galun and
M. Irani, Detecting
and Sketching the Common. IEEE
Conference on Computer Vision and Pattern
Recognition (CVPR), June 2010.
- E. Shechtman, A.
Rav-Acha, M. Irani and S. Seitz, Regenerative
Morphing. IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), June
2010. *See
webpage with examples and results.
- N. Ben-Eliezer, M.
Irani, and L. Frydman, Super-Resolved
Spatially Encoded Single-Scan 2D MRI. Magnetic
Resonance in Medicine 63:1594–1600 (2010).
- D. Glasner, S. Bagon,
and M. Irani, Super-Resolution
from a Single Image. International
Conference on Computer Vision (ICCV), October 2009. *See webpage with examples and results.
- S. Bagon, O. Boiman and M. Irani, What
is a Good Image Segment? A Unified Approach to Segment Extraction. European
Conference on Computer Vision (ECCV), October 2008. *See webpage with examples and results.
- D. Simakv, Y. Caspi, E. Shechtman and M. Irani, Summarizing
Visual Data Using Bidirectional Similarity. IEEE Conference on
Computer Vision and Pattern Recognition
(CVPR), June 2008. *See
webpage with example sequences and results .
- O. Boiman, E.
Shechtman and M.
Irani, In
Defense of Nearest-Neighbor Based Image Classification. IEEE Conference on
Computer Vision and Pattern Recognition
(CVPR), June 2008 .
- L. Gorelick, M. Blank, E.
Shechtman, M. Irani, and R. Basri, Actions
as Space-Time Shapes. In IEEE Transactions on Pattern Analysis and Machine Intelligence
(PAMI), 29(12): 2247-2253, December
2007. *See webpage with example sequences and results.
(A preliminary version of this
paper appeared in ICCV 2005.)
- O. Boiman
and M. Irani, Detecting
Irregularities in Images and in Video. International
Journal of Computer Vision (IJCV), 74(1), 17–31, August 2007. *See webpage with example sequences and results.
(A shorter version of this paper
appeared in ICCV 2005.)
- E. Shechtman
and M. Irani, Matching Local Self-Similarities across
Images and Videos.
IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), June 2007. *See webpage with example sequences and results .
- E. Shechtman and M.
Irani, Space-time
behavior based correlation – OR –
How to tell if two underlying motion fields are similar without
computing them? IEEE Transactions on Pattern Analysis and
Machine Intelligence (PAMI), 29(11): 2045-2056, November 2007. *See webpage with example sequences and results .
(A shorter version of this paper
appeared in CVPR 2005.)
- Y. Wexler, E. Shechtman and M.
Irani, Space-Time
Completion of Video .
In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),
March 2007. * See webpage with example sequences and results .
(A shorter version of this paper
appeared in CVPR 2004.)
- O. Boiman and
M. Irani, Similarity
by Composition. Neural Information
Processing Systems (NIPS), Vancouver, December 2006.
- Y. Ukrainitz and
M. Irani, Aligning
Sequences and Actions by Maximizing Space-Time Correlations. European
Conference on Computer Vision (ECCV), May
2006. *See
webpage with example sequences and results.
- L. Zelnik-Manor and M. Irani, On
single-Sequence and Multi-Sequence Factorizations. International
Journal of Computer Vision (IJCV),
67(3): 313-326, May 2006.
- L. Zelnik-Manor, M. Machline, and M. Irani, Multi-body
Factorization With Uncertainty: Revisiting Motion Consistency. International
Journal of Computer Vision (IJCV),
68(1): 27-41
(special issue on Vision and Modeling of Dynamics
Scenes), June 2006.
(A shorter version of this paper
appeared in VMODS Workshop -- Vision and Modelling of Dynamic Scenes --
June 2002.)
- Y. Caspi, D. Simakov,
and M. Irani, Feature-Based
Sequence-to-Sequence Matching. International
Journal of Computer Vision (IJCV),
68(1): 53-64
(special issue on Vision and Modeling of Dynamics
Scenes), June 2006. *See webpage with example sequences and results.
(A shorter version of this paper
appeared in VMODS Workshop -- Vision and Modelling of Dynamic Scenes -- June
2002.)
- L. Zelnik-Manor and M. Irani, Statistical
Analysis of Dynamic Actions.
IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI),
28(9): 1530--1535, September 2006.
(A preliminary version appeared in
CVPR’2001: “Event-Based video Analysis”).
- M. Blank, L. Gorelick,
E. Shechtman, M. Irani, and R. Basri, Actions
as Space-Time Shapes. IEEE
International Conference on Computer Vision (ICCV), Beijing, October
2005. *See
webpage with example sequences and results.
- E. Shechtman
and M. Irani, Space-Time
Behavior Based Correlation. IEEE Conference
on Computer Vision and Pattern Recognition
(CVPR), June 2005. *See
webpage with example sequences and results .
- E. Shechtman, Y. Caspi,
and M. Irani, Space-Time
Super-Resolution. IEEE
Trans. on Pattern Analysis and Machine Intelligence (PAMI), 27(4):
531-545, April 2005. *See webpage with example sequences and results .
(A shorter version of
this paper appeared in ECCV 2002, and received the Best Paper Award.)
- Y. Caspi and M.
Irani, Aligning
Non-Overlapping Sequences.
International Journal of Computer Vision (IJCV), Vol. 48, No. 1, pp. 39-51, 2002.
*See webpage
with example sequences and results.
(A shorter
version appeared in ICCV'2001).
* Received the Honorable
Mention for the 2001 Marr Prize.
- Y. Caspi and M. Irani, Spatio-Temporal Alignment of Sequences. IEEE Trans. on
Pattern Analysis and Machine Intelligence (PAMI), Vol. 24, No. 11, pp.
1409-1424, November 2002.
(A shorter version appeared in CVPR'2000:
"A step Towards Sequence-to-Sequence Alignment".)
*See webpage with
example sequences and results .
- M. Irani and P.
Anandan, Factorization
with Uncertainty .
European Conference on Computer Vision
(ECCV), June 2000.
* Received the best-paper prize at ECCV'2000.
Longer journal
version:
P. Anandan and M. Irani, Factorization
with Uncertainty .
International Journal of
Computer Vision (IJCV), 49(2-3):
101-116, September 2002.
- L. Zelnik-Manor and M. Irani, Event-Based
Video Analysis . IEEE
Conference on Computer Vision and Pattern
Recognition (CVPR), December 2001.
- M. Irani and P.
Anandan, About
Direct Methods. ICCV workshop on Vision
Algorithms, pp. 267-277, Corfu, September 1999.
- L. Zelnik-Manor and
M. Irani, Multi-View
Constraints on Homographies. IEEE Trans. on Pattern Analysis and Machine
Intelligence (PAMI), Vol. 24, No. 2, pp. 214 223, February 2002.
(A shorter version appeared in ICCV'1999.)
- M. Irani, P. Anandan,
and Meir Cohen, Direct
Recovery of Planar-Parallax from Multiple Frames . IEEE Trans. on Pattern Analysis
and Machine Intelligence (PAMI), Vol. 24, No. 11, pp. 1528 1534, November
2002.
(A shorter version appeared in ICCV'99
Workshop: Vision Algorithms 99, Corfu, September 1999.)
- L. Zelnik-Manor and
M. Irani, Multi-Frame
Estimation of Planar Motion . IEEE Trans. on Pattern
Analysis and Machine Intelligence (PAMI), Vol. 22, No. 10, pp. 1105-1116,
October 2000.
(A shorter version appeared in
CVPR'99: "Multi-frame alignment of planes").
- M. Irani, P. Anandan, J. Bergen, R. Kumar, and S. Hsu,
Efficient
Representations of Video Sequences and Their Applications . Signal Processing: Image Communication, special issue
on Image and Video Semantics: Processing, Analysis, and Application, Vol. 8,
No. 4, May 1996.
(A shorter version appeared in ICCV'1995:
M. Irani, P. Anandan, and S. Hsu, “Mosaic
based representations of video sequences and their applications”.)