Advanced Topics in Computer Vision Spring 2010

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17 Νοε 2013 (πριν από 3 χρόνια και 11 μήνες)

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Advanced Topics in Computer Vision Spring 2010


Topics and Papers



1.

Image and video descriptors:


Currently there are many papers under this topic

some of them will possibly be removed
. The
presenters will not be expected to go into all of the details,

but rather be familiar with the
different types of descriptors
.


Image Descriptors:



[
SIFT
]


Distinctive image features from scale
-
invariant keypoints
.
D. G. Lowe.

IJCV, 60(2):91

110, 2004.




[
GIST
]

Modeling the shape of the scene: a holistic representati
on of the
spatial envelope

Aude Oliva, Antonio Torralba International Journal of
Computer Vision, Vol. 42(3): 145
-
175, 2001



[
Shape
-
Context
]

Shape Matching and Object R
ecognition Using Shape
Contexts
,
PAMI April 2002
.



[
Geometric Blur
]

Geometric Blur for Template Matching


Computer Vision and
Pattern Recognition (CVPR) 2001, Hawaii, pp I.6
07
-
614



[
Local Self
-
Similarity
]


Matching Local Self
-
Similarities across Images and
Videos
.



E. Shechtman

and


M. Irani
IEEE Conference on Computer Vision
and


Pattern Recognition (CVPR), June 2007.




[
SURF
]

"SURF: Speeded Up Robust Features
"
,
Herbert Bay
,
Andreas Ess,
Tinne Tuytelaars, Luc Van Gool Computer Vision and Image Understanding
(CVIU), Vol. 110, No. 3, pp. 346
--
359, 2008



[
LBP
]

Description of interest regions with local binary pat
terns.



M. Heikkila,
M. Pietikainen and C. Schmid.

Pattern Recognition

Volume 42, Issue 3
, March
2009, Pages 425
-
436


Video Descriptors:



[
Space
-
time
Local Self
-
Similarity
]




[
Space
-
time corners
]

"
On Space
-
Time Interest Points
"
I. Laptev;



International
Journal of Computer Vision
, vol 64, number 2/3
(2005)
,


OR . Laptev and T.
Lindeberg; in
Proc. ICCV'03, Nice, France, pp.I:432
-
439.



[
Space
-
Time SIFT
]

Survey

/ comparison papers for d
ifferent applications (recognition / matching):



Local features and kernels for classification of texture and object categories: a
comprehensive study.



J. Zhang, M. Marszalek, S. Lazebnik and C.

Schmid.

International Journal of Computer Vision, 73(2):213
-
238, 2007.



A performance evaluation of local descriptors
. K. Mikolajczyk and C. Schmid.

PAMI, 27(10):1615

1630, 2005
.



Comparing local feature descriptors in pLSA
-
based image models
.

E. Horster
,
T. Greif, R. Lienhart, and M. Slaney. DAGM
,
2008.



2.

Exploiting wealth of huge image libraries for solving Computer Vision problems:





James Hays, Alexei A. Efros. Scene Completion Using Millions of Photographs. ACM
Transactions on Graphics (SIGGRAPH

2007). August 2007, vol. 26, No. 3.

http://graphics.cs.cmu.edu/projects/scene
-
completion/scene
-
completion.pdf



Simon, I. and Seitz, S. M.. Scene Segmentation Using t
he Wisdom of Crowds. ECCV
2008.

http://grail.cs.washington.edu/pub/papers/simon08ss.pdf



D. Bitouk, N. Kumar, S. Dhillon, P. N. Belhumeur, and S. K. Nayar,


"Face Swapping:
Automatical
ly Replacing Faces in Photographs,"


ACM Trans. on Graphics (also Proc.
of ACM SIGGRAPH),


Aug, 2008.

http://www1.cs.columbia.edu/CAVE/publications/./pdfs/Bitouk_SIGGRA
PH08.pdf




J. Hays,


A. Efros. IM2GPS: estimating geographic information from a single image.


IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2008.

http://graphics.cs.cm
u.edu/projects/im2gps/


3.

Efficient search in large imagery databases:





A. Torralba, R. Fergus, W. T. Freeman, "80 million tiny images: a large dataset for
non
-
parametric object and scene recognition", PAMI 2008.

http://people.csail.mit.edu/torralba/tmp/tiny.pdf



A. Torralba, R. Fergus, Y. Weiss, "Small codes and large databases for recognition",
CVPR 2008.

http
://people.csail.mit.edu/torralba/publications/cvpr2008.pdf





Yair Weiss,

Antonio Torralba,

Rob Fergus,


"Spectral Hashing"
--

NIPS 2008

http://books.nips.cc/papers/files/nips21/N
IPS2008_0806.pdf



D. Nister and H. Stewenius. Scalable recognition with a vocabulary tree. IEEE Conf. on
Computer Vision and Pattern Recognition (CVPR), pages 2161

2168, 2006.

http://www.vis.uky.edu/~stewe/publications/nister_stewenius_cvpr2006.pdf



N. Kumar, P. N. Belhumeur, and S. K. Nayar,


"FaceTracer: A Search Engine for Large
Collections of Images with Faces," European Conference on Computer Vision
(ECCV),


pp.34
0
-
353, Oct, 2008.

http://www1.cs.columbia.edu/CAVE/publications/./pdfs/Kumar_ECCV08.pdf



4
.

Statistics of
Natural I
mages:





S. C. Zhu and D. Mumford. Prior learning and g
ibbs reaction
-
diffusion. IEEE PAMI,
19(11):1236

1250, 1997.

http://www.stat.ucla.edu/~sczhu/papers/Generic_prior.pdf



S. Roth and M. J. Black. Fields of experts: A framework for lear
ning image priors. In
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2005.

http://www.gris.informatik.tu
-
darmstadt.de/~sroth/pubs/cvpr05roth.pdf

(Th
ere is also a longer and more detailed journal version
--

IJCV'09:
http://www.gris.informatik.tu
-
darmstadt.de/~sroth/pubs/foe
-
ijcv.pdf
)



Y. Weiss and W. T. Freeman. What m
akes a good model of natural images. In IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),


2007.

http://www.cs.huji.ac.il/~yweiss/foe
-
final.pdf


5
.

Blind Deconvolution





H
Attias.
Independent factor analysis
.
Neural Computation

(Article) 11, 803
-
851, 1999.

http://www.goldenmetallic.com/research/ifa.pd
f



R. Fergus, B. Singh, A. Hertzmann, S.T. Roweis, and W.T.

Freeman. Removing
camera shake from a single photograph. SIGGRAPH, 2006



N. Joshi, R. Szeliski, and D. Kriegman. Psf estimation using sharp edge prediction. In
CVPR, 2008



LEVIN, A., WEISS, Y., DURA
ND, F., AND FREEMAN, W. 2009.

Understanding and evaluating blind deconvolution algorithms. In CVPR.



6
.

Lightfield







Marc Levoy and Patrick M. Ha
nrahan. Light field rendering. In SIGGRAPH, 1996.



Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, and Michael F. Cohen. The
lumigraph. SIGGRAPH ’96: Proceedings of the 23rd annual conference on Computer
graphics and interactive techniques, pages 4
3

54, New York, NY, USA, 1996. ACM



J. Chai, X. Tong, S. Chan, and H. Shum. Plenoptic sampling. SIGGRAPH, 2000.



Aaron Isaksen, LeonardMcMillan, and Steven J. Gortler. Dynamically reparameterized
light fields. SIGGRAPH, 2000.



Ren Ng. Fourier slice photograph
y. SIGGRAPH, 2005.



7
.

Coded Aperture







Zhou, C., Nayar, S.K.: What are Good Apertures for Defocus Deblurring? In: IEEE
International Conference on Computational Photography. (2009)



Zhou, C., Lin, S., Nayar, S.K.: Coded Aperture Pairs for Depth from Def
ocus. In:
ICCV. (2009)



Levin, A., Fergus, R., Durand, F., Freeman,W.: Image and depth from a conventional
camera with a coded aperture. SIGGRAPH (2007)



Veeraraghavan, A., Raskar, R., Agrawal, A., Mohan, A., Tumblin, J.: Dappled
photography: Mask
-
enhanced c
ameras for heterodyned light fields and coded aperture
refocusing. SIGGRAPH (2007)



8
.

Compressed sensing




Compressive sensing, matrix completion




Emmanuel Candes and Michael Wakin,

An introduction to compressive sampling,
IEEE Signal Processing Magazi
ne, 25(2), pp. 21
-

30, March 2008.




http://www
-
stat.stanford.edu/~candes/papers/MatrixCompletion.pdf




Also may be of interest

http://www
-
stat.stanford.edu/~candes/papers/RobustPCA.pdf




[SFM with sparsity:]

http://www.maths.lth.se/vision/publdb/reports/pdf/
olsson
-
oskarsson
-
scia
-
09.pdf




[Face recognition with sparsity:]

http://watt.csl.illinois.edu/~yima/psfile/PAMI
-
Face.pdf





9
.

Sparse Representations





Dictionaries for sparse

representation

modeling:




M. Aharon, M. Elad, and A. M. Bruckstein, “The K
-
S
VD: an algorithm for designing
of overcomplete diction
aries for sparse representation

,
IEEE Trans. Signal Process.,
vol. 54, no. 11, pp. 4311

4322, 2006.




http://www.cs.technion.ac.il/~elad/publications/journals/2006/Review_Paper_SIAM_R
eview.pdf




http://www.cs.technion.ac.il/~elad/publications/journals/200
5/34_KSVD_LAA.pdf




http://www.cs.technion.ac.il/~elad/publications/journals/2009/IEEE_Proc_Dictionary.p
df




10
.

Graph
-
Cut



using higher
-
order potent
ials





Yuri Boykov, Olga Veksler, Ramin Zabih, Fast Approximate Energy Minimization via
Graph
-
Cuts

IEEE transactions on PAMI, vol. 20, no. 12, p. 1222
-
1239, November 2001

http://www
.csd.uwo.ca/faculty/olga/Papers/pami01_final.pdf



Pushmeet Kohli, M Pawan Kumar, Philip Torr P3 & Beyond: Solving Energies with
Higher Order Cliques. CVPR 2007.

http:/
/research.microsoft.com/en
-
us/um/people/pkohli/papers/cvpr07.pdf



Carsten Rother, Pushmeet Kohli, Wei Feng, Jiaya Jia Minimizing Sparse Higher Order
Energy Functions of Discrete Variables. CVPR 2009.

http://research.microsoft.com/en
-
us/um/people/pkohli/papers/rkfj_cvpr09.pdf



Pushmeet Kohli, Lubor Ladicky, Philip Torr Robust Higher Order Potentials for
Enforcing Label Consistency. IJCV 2009.

http://research.microsoft.com/en
-
us/um/people/pkohli/papers/klt_IJCV09.pdf

11
.

Graph
-
Cut



using
using non
-
submodular functions






Vladimir Kolmogorov

and
Ramin Zabih



“What Energy Functions can be Minimized via
Graph Cuts?”.

In
IEEE Transactions on Pattern Analysis and Machine Intelligence

(
PAMI
),
26(2):147
-
159, February 2004.


http://www.cs.ucl.ac.uk/staff/V.Kolmogorov/papers/KZ
-
PAMI
-
graph_cuts.pdf



(2)


Vladimir Kolmogorov

and
Cartsen Rother
.


“Minimizing non
-
submodular functions with
graph cuts
-

a review”


In
IEEE Transactions on Pattern Analysis and Machine Intelligence

(
PAMI
), 29(7):1274
-
1279, July 2007.

http://w
ww.cs.ucl.ac.uk/staff/V.Kolmogorov/papers/KR
-
PAMI07.pdf



"Exact Optimization for Markov Random Fields with Convex Priors" Hiroshi Ishikawa,


IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 10, pp. 1333
-
1336, Oct. 2003.

12.

Action Recognition



Dynamic
:



I.

Laptev
,

M.

M
arszałek
,

C.

Schmid

Learning realistic human actions from
movies.

CVPR 2008.

http://www.irisa.fr/vista
/Papers/2008_cvpr_laptev.pdf



Lena Gorelick, Moshe Blank,

Eli Shechtman,

Michal Irani, and

Ronen Basri. Actions
as Space
-
Time Shapes.

PAMI 2007

http://www.wisdom.weizmann.ac.il/~vision/VideoAnalysis/Demos/SpaceTimeActions/
SpaceTimeActions_pami07.pdf



I. Laptev and P. Pérez. Retrieving actions in movies, ICCV 2007

http://www.irisa.fr/vista/Papers/2007_iccv_laptev.pdf

Static:



Abhinav Gupta
,

Aniruddha Kembhavi
,

Larry S. Davis
,

Observing Human
-
Object
Interactions: Using Spatial and Funct
ional Compatibility for Recognition
, PAMI,
October 2009 (vol. 31 no. 10)

pp. 1775
-
1789

http://www.computer.org/portal/web/csdl/doi?doc=doi/10.1109/TPAMI.2
009.83




Li
-
Jia Li,

Li Fei
-
Fei,
What, where and who? Classifying events by scene and object
recognition.

ICCV 2007

http://vision.stanford.edu/documents/LiFei
-
Fei_ICCV07.
pdf