*Fornay, G.D.*,

**The Viterbi Algorithm**,

*PIEEE(61)*, No. 3, March 1973, pp. 268-277.
An algorithm to compute the optimal (most likely) state sequence in
a hidden Markov model given a
sequence of observed outputs. (in TN**2 steps).
See also Error bounds for convolutional codes and an asymptotically optimal decoding algorithm.
BibRef
**7303**

*Barrow, H.G.*, and
*Tenenbaum, J.M.*,

**Computational Vision**,

*PIEEE(69)*, No. 5, May 1981, pp. 572-595.
BibRef
**8105**

*Brady, M.*,

**Computational Approaches to Image Understanding**,

*Surveys(14)*, No. 1, March 1982, pp. 3-71.
BibRef
**8203**

And:
*MIT AI Memo*-653, October 1981.
*Survey, Computational Vision*.
*Computational Vision, Survey*. Survey of much of the DARPA research (up to early 81).
Concentrates on general processing techniques and ignores
applications. Separates the descriptions based on the level of
representation being used, especially those that relate to 3-D
descriptions. Mostly a review of MIT work with references to other
similar and related work, but little unrelated work.
Good references on topics covered.
BibRef

*Brady, M.[Mike]*,

**Toward a Computational Theory of Early Visual Processing in Reading**,

*MIT AI Memo*-593, September 1980.
BibRef
**8009**

*Ullman, S.*,

**Visual Routines**,

*Cognition(18)*, 1984, pp. 97-156.
BibRef
**8400**
*RCV87*(298-328).
BibRef

And:
*MIT AI Memo*-723, June 1983.
BibRef

And:

**Visual Routines: Where bottom-Up and Top-down Processing Meet**,

PR(2), 1986, pp. 159-213.
This second reference cannot be correct, not for the Pattern Recognition
journal.
General discussion of the later processing of visual information.
BibRef

*Lee, D.*,

**Some Computational Aspects of Low-Level Computer Vision**,

*PIEEE(76)*, No. 8, August 1988, pp. 890-898.
BibRef
**8808**

*Uttal, W.R.*,
*Liu, N.*, and
*Kalki, J.*,

**An Integrated Computational Model of Three-Dimensional Vision**,

*SV(9)*, 1996, pp. 393-422.
BibRef
**9600**

*Ritter, G.X.*, (Guest ed.),

**Special Issue on Mathematical Imaging**,

*JMIV(5)*, No. 4, December 1995, 275-358.
BibRef
**9512**

*Jobson, D.J.*,
*Rahman, Z.U.*,
*Woodell, G.A.*,

**Properties and Performance of a Center/Surround Retinex**,

*IP(6)*, No. 3, March 1997, pp. 451-462.

IEEE DOI
**9703**

BibRef

*Daugman, J.G.*,

**Neural Image-Processing Strategies Applied in
Real-Time Pattern-Recognition**,

*RealTimeImg(3)*, No. 3, June 1997, pp. 157-171.
**9708**

BibRef

*Fejes, S.*,
*Rosenfeld, A.*,

**Migration Processes I: the Continuous Case**,

*JMIV(8)*, No. 1, January 1998, pp. 5-25.

DOI Link
**9803**

BibRef

*Fejes, S.*,
*Rosenfeld, A.*,

**Migration Processes II: the Discrete Case**,

*JMIV(8)*, No. 1, January 1998, pp. 27-40.

DOI Link
**9803**

BibRef

*Fejes, S.*,
*Rosenfeld, A.*,

**Migration Processes**,

*ICPR96*(II: 345-349).

IEEE DOI
**9608**

(Univ. of Maryland, USA)
BibRef

*Fejes, S.*,

**Migration Processes: Theory and applications**,

*UMD*Technical report. CS-TR-3603, CAR-TR-813TR, November 1995.

WWW Link.
BibRef
**9511**

*Ritter, G.X.*,
*Shi, H.C.*,

**Special Section on Advances in Mathematical Imaging**,

*JEI(6)*, No. 4, October 1997, pp. 393-394.
**9807**

BibRef

*Zhu, S.C.[Song Chun]*,
*Yuille, A.L.[Alan L.]*,
*Mumford, D.[David]*,

**Guest Editorial: Statistical and Computational Theories of Vision:
Modeling, Learning, Sampling and Computing, Part I**,

*IJCV(40)*, No. 1, October 2000, pp. 5-6.

DOI Link
**0101**

Introduction to the special issue.
BibRef

*Abubakar, A.*,
*van den Berg, P.M.*,

**Total variation as a multiplicative constraint for solving inverse
problems**,

*IP(10)*, No. 9, September 2001, pp. 1384-1392.

IEEE DOI
**0108**

BibRef

*Cohen, L.D.[Laurent D.]*,

**Guest Editorial: Special Issue on Mathematics and Image Analysis**,

*JMIV(20)*, No. 1-2, January-March 2004, pp. 5-5.

DOI Link
**0403**

BibRef

*Cohen, L.D.[Laurent D.]*,

**Guest Editorial**,

*JMIV(25)*, No. 3, October 2006, pp. 287.

Springer DOI
**0611**

Special issue intro.
BibRef

*Cohen, L.D.[Laurent D.]*,
*Sochen, N.A.[Nir A.]*,
*Vese, L.A.[Luminita A.]*,

**Guest Editorial, Special Issue Introduction**,

*JMIV(33)*, No. 2, February 2009, pp. xx-yy.

Springer DOI
**0903**

BibRef

*Prabhu, N.[Nagabhushana]*,
*Chang, H.C.[Hung-Chieh]*,
*de Guzman, M.[Maria]*,

**Optimization on Lie manifolds and pattern recognition**,

*PR(38)*, No. 12, December 2005, pp. 2286-2300.

Elsevier DOI
**0510**

Reduce vision problem to optimizing nonlinear function over a Lie manifold.
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*Han, Y.*,

**Newton type algorithm on Riemannian manifolds applied to robot vision,
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*VISP(152)*, No. 3, June 2005, pp. 275-282.

DOI Link
**0510**

BibRef

*Kragic, D.[Danica]*,
*Kyrki, V.[Ville]*, (Eds.)

**Unifying Perspectives in Computational and Robot Vision**,

*Springer*2008, ISBN: 978-0-387-75521-2
*Survey, Computational Vision*.

WWW Link.
**Buy this book: Unifying Perspectives in Computational and Robot Vision (Lecture Notes in Electrical Engineering)
**
BibRef
**0800**

*Kokkinos, I.[Iasonas]*,
*Yuille, A.L.[Alan L.]*,

**Inference and Learning with Hierarchical Shape Models**,

*IJCV(93)*, No. 2, June 2011, pp. 201-225.

WWW Link.
**1104**

BibRef

Earlier:

**HOP: Hierarchical object parsing**,

*CVPR09*(802-809).

IEEE DOI
**0906**

BibRef

And:

**Inference and learning with hierarchical compositional models**,

*SIG09*(6-6).

IEEE DOI
**0906**

BibRef

*Yuille, A.L.*,

**Towards a theory of compositional learning and encoding of objects**,

*ITCVPR11*(1448-1455).

IEEE DOI
**1201**

BibRef

*Kokkinos, I.[Iasonas]*,
*Maragos, P.[Petros]*,
*Yuille, A.L.[Alan L.]*,

**Bottom-Up and Top-down Object Detection using Primal Sketch Features
and Graphical Models**,

*CVPR06*(II: 1893-1900).

IEEE DOI
**0606**

BibRef

*Kokkinos, I.[Iasonas]*,
*Deriche, R.[Rachid]*,
*Maragos, P.[Petros]*,
*Faugeras, O.D.[Olivier D.]*,

**A Biologically Motivated and Computationally Tractable Model of Low and
Mid-Level Vision Tasks**,

*ECCV04*(Vol II: 506-517).

Springer DOI
**0405**

BibRef

*Gill, P.R.[Patrick R.]*,

**Enabling a computer to do the job of a lens**,

*SPIE(Newsroom)*, September 4, 2013.

DOI Link
**1310**

A new kind of diffractive phase grating permits computational imaging
of polychromatic distant objects in situations where focal optics are
not convenient.
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*Yang, C.H.[Chang-Huei]*,

**Computational microscopy improves resolution, field of view**,

*SPIE(Newsroom)*, October 23, 2013.

DOI Link
**1310**

A complete data set derived from low-resolution snapshots could lead
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*Mitra, K.[Kaushik]*,
*Cossairt, O.S.[Oliver S.]*,
*Veeraraghavan, A.[Ashok]*,

**A Framework for Analysis of Computational Imaging Systems:
Role of Signal Prior, Sensor Noise and Multiplexing**,

*PAMI(36)*, No. 10, October 2014, pp. 1909-1921.

IEEE DOI
**1410**

Gaussian processes
BibRef

*Cossairt, O.S.[Oliver S.]*,
*Mitra, K.[Kaushik]*,
*Veeraraghavan, A.[Ashok]*,

**Analyzing computational imaging systems**,

*SPIE(Newsroom)*, November 19, 2013.

DOI Link
**1311**

A novel framework, which takes into account optical multiplexing,
sensor noise characteristics, and signal priors, can analyze any
linear computational imaging camera.
BibRef

*Mitra, K.[Kaushik]*,
*Cossairt, O.S.[Oliver S.]*,
*Veeraraghavan, A.[Ashok]*,

**Can we beat Hadamard multiplexing? Data driven design and analysis
for computational imaging systems**,

*ICCP14*(1-9)

IEEE DOI
**1411**

Gaussian processes
BibRef

*Greengard, S.[Samuel]*,

**Seeing the Big Picture**,

*CACM(56)*, No. 12, December 2013, pp. 16-18.

DOI Link
**1312**

Lensless cameras and other advances in digital imaging, computational
optics, signal processing, and big data are transforming how we think
about photography.
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*Rasanen, O.*,
*Kakouros, S.*,

**Modeling Dependencies in Multiple Parallel Data Streams with
Hyperdimensional Computing**,

*SPLetters(21)*, No. 7, July 2014, pp. 899-903.

IEEE DOI
**1405**

Context
BibRef

IEEE DOI

Find good (artistic composition) sub views. BibRef

*Soatto, S.[Stefano]*,

**Actionable information in vision**,

*ICCV09*(2138-2145).

IEEE DOI
**0909**

Complexity not of the image itself, but the image after removal of
effects of viewpoint and illumination.
BibRef

*Franc, V.[Vojtech]*,
*Hlavác, V.[Václav]*,
*Navara, M.[Mirko]*,

**Sequential Coordinate-Wise Algorithm for the Non-negative Least Squares
Problem**,

*CAIP05*(407).

Springer DOI
**0509**

*Least Squares*. The proposed algorithm showed promising performance in comparison
to the Landweber method.
BibRef

*Fischer, S.[Sylvain]*,
*Bayerl, P.[Pierre]*,
*Neumann, H.[Heiko]*,
*Cristóbal, G.[Gabriel]*,
*Redondo, R.[Rafael]*,

**Are Iterations and Curvature Useful for Tensor Voting?**,

*ECCV04*(Vol III: 158-169).

Springer DOI
**0405**

Add iterations and curvature enhancements.
See also Curvature-Augmented Tensor Voting for Shape Inference from Noisy 3D Data.
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*Nayar, S.K.*,

**Computational Imaging**,

*ICIP01*(Invited Talk, Computational Imaging).
**0108**

Not in proceedings.
BibRef

*Woodham, R.J.*,

**A Computational Approach to Remote Sensing**,

*CVPR85*(2-12).
(UBC) Nice discussion of various techniques.
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**8500**

*Edelman, S.[Shimon]*,
*Weinshall, D.[Daphna]*,

**Computational Vision: A Critical Review**,

*MIT AI Memo*-1158, October 1989.
BibRef
**8910**

*Thompson, W.B.[William B.]*, and
*Yonas, A.[Albert]*,

**What Should be Computed In Low Level Vision Systems**,

*AAAI-80*(7-10).
BibRef
**8000**

*Hildreth, E.C.[Ellen C.]*,
*Ullman, S.[Shimon]*,

**The Computational Study of Vision**,

*MIT AI Memo*-1038, April 1988.

WWW Link.
BibRef
**8804**

*Hildreth, E.C.[Ellen C.]*,
*Hollerbach, J.M.[John M.]*,

**The Computational Approach to Vision and Motor Control**,

*MIT AI Memo*-846, August 1985.

WWW Link.
BibRef
**8508**

*Hollerbach, J.M.[John M.]*,

**Hierarchical Shape Description of Objects by Selection and
Modification of Prototypes**,

*MIT AI-TR*-346 November 1975.

WWW Link.
BibRef
**7511**

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in

Physics Based Vision .

Last update:Mar 2, 2019 at 12:07:42