Code for Computer Vision Algorithms

The standard source for code to implement basic computer vision algorithms is the OpenCV Library from Intel. Many research groups build on top of this OpenCV code base. The avaliability of code for specific techniques or applications is harder to predict, but some implementations are made available by the authors and others are available from commercial vendors. The following pointers are organized somewhat by what the code does, and often by what the code is written in. If you follow the link for the reference you may find many related papers in the Computer Vision Bibliography. A number of lists of code for sub-areas (e.g. OCR) have been created by researchers in the past, but often these are no longer maintained. These lists are included in the above listing along with many of the individual entries in those lists. Current research and applications are highlighted in various general and topical Computer Vision and Image Processing conferences, especially applications workshops.

Related resources include:

Code Source References, Listed by Topic

For more information on the topics, contact information, etc. see the annotated Computer Vision Bibliography or the Complete Conference Listing for Computer Vision and Image Analysis

Detailed Entries for Code

Bouguet, J.Y.,
Matlab Camera Calibration Toolbox,
TRCalTech, 2000.
HTML Version. Code, Camera Calibration. BibRef

Marquardt, D.,
An Algorithm for Least-Squares Estimation of Nonlinear Parameters,
SIAM_JAM(11), 1963, pp. 431-441. Levenberg-Marquardt is a popular alternative to the Gauss-Newton method of finding the minimum of a function F(x) that is a sum of squares of nonlinear functions.
HTML Version. Code, Levenberg-Marquardt. BibRef

Lourakis, M.I.A.[Manolis I.A.], and Argyros, A.A.,
The Design and Implementation of a Generic Sparse Bundle Adjustment Software Package Based on the Levenberg-Marquardt Algorithm,
TR340, Institute of Computer Science - FORTH, Heraklion, Crete, Greece, August, 2004. (updated August 2009).
WWW Version. Code, Bundle Adjustment. Publicly available (GPL) C/C++ software package for generic sparse bundle adjustment based on the Levenberg-Marquardt algorithm. BibRef

Lourakis, M.I.A.[Manolis I.A.],
Levenberg-Marquardt nonlinear least squares algorithms in C/C++,
OnlineApril 2009.
WWW Version. Code, Levenberg-Marquardt. Publicly available (GPL) C/C++ software package for Levenberg-Marquardt algorithm. BibRef

El-Sheimy, N.[Naser],
Addingham Bundle Adjustment,
Online2007. University Calgary.
HTML Version. Code, Bundle Adjustment. BibRef

Tsai, R.Y.,
A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses,
RA(3), No. 4, 1987, pp. 323-344. Code, Camera Calibration. Code:
HTML Version. BibRef
Earlier:
An Efficient and Accurate Camera Calibration Technique for 3-D Machine Vision,
CVPR86(364-374). Lens Distortions. This was the "best" paper at the conference. Various techniques for calibration and error analysis. Use 60 Control points to derive camera parameters (position, orientation, focal length, radial lens distortion, and image scanning parameters). Compute intrinsic and extrinsic parameters using a planar or non-planar test pattern. Criticized for not using rigorous least-squares method. BibRef

Mitsunaga, T.[Tomoo], Nayar, S.K.[Shree K.],
Radiometric Self Calibration,
CVPR99(I: 374-380).
IEEE Abstract.
WWW Version.
PDF Version. Code, Radiometric Calibration.
WWW Version. BibRef

Zhang, Z.Y.[Zheng-You],
A Flexible New Technique for Camera Calibration,
PAMI(22), No. 11, November 2000, pp. 1330-1334.
IEEE Abstract.
WWW Version.
BibRef
And: MicrosoftMSR-TR-98-71, December 1998.
Postscript Version. Code, Camera Calibration. And for Code:
WWW Version. Planar pattern in at least 2 orientations. BibRef

OpenCV,
IntelSeptember 2009. Code, Image Processing. Code, Computer Vision. Code, Image Processing, C. Code, Open Source.
WWW Version. And the Source Forge reference:
WWW Version. Version 2.0 released in 2009. C and C++ interfaces. Original version was August 2000. The standard open source code for many basic computer vision tasks. Support and development from See also Willow Garage. BibRef

ImageJ: Image Processing and Analysis in Java,
2007. Code, Image Processing. Code, Image Processing, Java.
WWW Version. A set of public domain image (US Government code) analysis routines in Java.

ImageJ-Plugins -- Various Plugins for the image manipulation software ImageJ,
2007. Code, Image Processing. Code, Image Processing, Java.
HTML Version. See also University of Freiburg.

Image Processing Library 98,
2003.
WWW Version. Code, Image Analysis. Code, Image Processing, C++. A platform independent image manipulating C/C++ library.

Recognition And Vision Library,
2003.
WWW Version. Code, Image Analysis. Code, Image Processing, C++. C++ class library together with a range of computer vision, pattern recognition, audio and supporting tools. See also University of Surrey.

C++ Template Image Processing Library,
2000.
WWW Version. Code, Image Analysis. Code, Image Processing, C++. Code, Open Source. INRIA derived code.

ImageLib: An Image Processing C++ Class Library,
2000.
WWW Version. Code, Image Analysis. Code, Image Processing, C++. C++ class library providing image processing and related facilities. See also University of Cape Town.

NeatVision,
2000. Code, Image Analysis.
WWW Version. Code, Image Processing, Java. NeatVision is a free Java based image analysis and software development environment, which provides high level access to a wide range of image processing algorithms. From: See also Dublin City University, Machine Vision Group.

The Delft Image Processing library,
2000.
WWW Version. Code, Image Analysis. Code, Image Analysis, Matlab. Code, Image Analysis, C. DIPimage is a MATLAB toolbox. DIPlib is a platform independent scientific image processing library written in C. Formerly ImLib3D From: See also Delft University of Technology.

LibCVD: computer vision library,
2009.
HTML Version. Code, Image Analysis. Code, Image Processing, C++. Portable C++ library providing image processing and related facilities.

PEIPA Computer Vision Software,
Online2004.
HTML Version. Code, Computer Vision. Dataset. Pilot European Image Processing Archive. This lists a number of sources for various alogrithms. They also include pointers to the usual set of image databases. BibRef

LTI-Lib,
Online2005.
WWW Version. Code, Image Processing. Code, Image Processing, C++. Code, Open Source. Object oriented library with algorithms and data structures frequently used in image processing and computer vision. See also Aachen University of Technology. BibRef

Mimas,
January, 2006.
WWW Version. Code, Image Processing. Code, Image Processing, C++. Code, Open Source. C++ toolkit, corners, etc.

MediaCybernetics,
2005. Vendor, Software. Code, Image Processing.
WWW Version. A set of Image Analysis products, especially applied to microscope images and scientific applications.

Bioimage Suite,
1998.
WWW Version. Code, Image Processing. Yale group. Biomedical imaging and visualization.

Noesis Vision,
2007.
HTML Version. Code, Image Analysis. Primarily bio, chemistry, but others. Visilog product

Generic Programming for Computer Vision: The VIGRA Computer Vision Library,
OnlineDecember, 2006. Code, Image Processing. Code, Image Processing, C++. C++ implementation, using standard template library. BibRef

Bailey, D.G., Hodgson, R.M.,
VIPS: A Digital Image Processing Algorithm Development Environment,
IVC(6), No. 3, August 1988, pp. 176-184.
WWW Version. Code, Image Processing.
WWW Version. See also University of Southampton. BibRef

Kovesi, P.[Peter],
MATLAB and Octave Functions Software for Computer Vision and Image Processing,
Online2007. Code, Computer Vision. Code, Computer Vision, Matlab.
WWW Version. See also University of Western Australia. BibRef

VXL,
Online2004.
WWW Version. Code, Computer Vision. Code, Computer Vision, C++. Code, Open Source. VXL (the Vision-something-Libraries) is a collection of C++ libraries designed for computer vision research and implementation. It was created from TargetJr and the IUE with the aim of making a light, fast and consistent system. BibRef

LibTIFF: TIFF Library and Utilities,
Code, Image Processing. Code, TIFF.
WWW Version. The Tag Image File Format (TIFF) pages. The site is now maintained through See also OSGeo: Open Source Geospatial Foundation.

pbmplus Image File Format Conversion Package,
2001 Code, Image Processing. PBMPlus.
WWW Version. The standard toolkit for command line conversion of image formats. Everything to everything else.

IFS: Image File System,
Code, Image Processing.
HTML Version. Variety of image handling rountines. From NCSU

ImageMagick,
1999. Code, Image Processing.
WWW Version. A software suite to create, edit, and compose bitmap images. Command line and libraries called from your programs.

GNU Image Manipulation Program,
2001 Code, Image Processing.
WWW Version. The GNU based (i.e. free) set of image manipulation programs intended to compete with the more expensive professional programs. Almost, but not quite Photoshop.

Skiljan, I.[Ifran],
Ifran View,
Online1996. Code, Image Processing.
WWW Version. A useful basic image processing tool. Not too fancy, but does a lot of basic tasks. Includes batch mode processing for a list of files. BibRef

Rad Video Tools,
1988. Code, Video Processing. A package of tools for game developers, but also includes a package of video tools for conversions and other operations.

Supercomputing Systems: Vision,
2000. Code, Image Processing.
HTML Version. Image processing systems. leanXcam.

Landy, M.S.[Michael S.], Cohen, Y.[Yoav], and Sperling, G.[George],
HIPS: A Unix-Based Image Processing System,
CVGIP(25), No. 3, March 1984, pp. 331-347.
WWW Version. Code, Image Processing.
HTML Version. BibRef
And:
HIPS: Image Processing Under UNIX. Software and Applications,
BehResMeth(16), No. 2, 1984, pp. 199-216. The system is commercially available. BibRef

Groningen Image Processing System, GIPSY,
TR1992.
WWW Version. System: Gipsy. Code, Image Processing. There are 2 systems by the same name. They are different. BibRef

Pope, A.R., Lowe, D.G.,
Vista: A Software Environment for Computer Vision Research,
CVPR94(768-772).
IEEE Abstract. System: Vista. Code, Image Analysis.
HTML Version. BibRef

Whittenburg, T.,
Photo-Based 3D Graphics in C++: Compositing, Warping, Morphing, and Other Digital Special Effects,
John Wiley& Sons, 1995, ISBN 0-471-04972-7. Code, Image Processing. Code, Image Processing, C++. Contains a disk with the programs. Buy this book: Photo-Based 3d Graphics in C++: Compositing, Warping, Morphing and Other Digital Special Effects/Book and Disk BibRef

Dobie, M.R., Lewis, P.H.,
Data Structures for Image Processing in C,
PRL(12), 1991, pp. 457-466. Code, Image Processing. Code, Image Processing, C. BibRef

OpenVidia,
Online2006.
WWW Version. Code, Open Source. Code, GPU. Code, Computer Vision. Opensource computer vision algorithms for computer graphics hardware. Uses OpenGL, Cg, CUDA. Primarily from the Toronto group. See also University of Toronto. BibRef

GPU4Vision,
Online2009.
WWW Version. Code, Computer Vision. Code, GPU. Opensource computer vision algorithms for NVIDIA hardware. See also Graz University of Technology. BibRef

Shirahatti, N.V.[Nikhil V.], Barnard, K.[Kobus],
Evaluating Image Retrieval,
CVPR05(I: 955-961).
IEEE DOI Link

HTML Version. Code, Image Retrieval. Dataset, Image Retrieval. BibRef

Photosynth,
2008.
WWW Version. Code, Mosaic. Vendor, Database. The Photosynth system builds on the Seadragon system but is primarily the University of Washington work on synthesis of scenes Assembles multiple images into a single whole, not exactly mosaicing. Available for download. See also Multi-View Stereo for Community Photo Collections. See also Microsoft Research.

Gulshan, V.[Varun],
Implementation of the Self-Similarity Descriptor,
Online2007
WWW Version. Code, Matching. BibRef

Berry, R.[Richard], Burnell, J.[James],
Handbook of Astronomical Image Processing,
Willmann-Bell2005.
HTML Version. Code, Image Processing. Includes the Astronomical Image Processing package. BibRef

Paulus, D., and Hornegger, J.,
Pattern Recognition and Image Processing in C++,
ViewegBraunschweig (Germany), 1995 Algorithms. Object-Oriented Programming. Code, Image Processing. Code, Image Processing, C++.
HTML Version. BibRef

Fisher, R.B.[Robert B.], (Ed.)
HIPR2: Free WWW-based Image Processing Teaching Materials with JAVA,
Online Book2000.
BibRef Edinburgh Code, Image Processing. Code, Image Processing, Java. Department of Artificial Intelligence University of Edinburgh, UK. A collection of Image Processing examples -- with Java to be run through the web. For teaching. The 50 most common classes of image processing operations. How they work, when to use them, examples and java.
WWW Version. BibRef

Fisher, R.B.[Robert B.], Perkins, S.[Simon], Walker, A.[Ashley], Wolfart, E.[Erik],
Hypermedia Image Processing Reference,
A complete online tutorial for image processing, available on CD-ROM from John Wiley& Sons, 1996. Code, Image Processing. Demonstration version: BibRef Edinburgh
WWW Version. BibRef

Parker, J.R.,
Algorithms for Image Processing and Computer Vision,
Wiley1996. ISBN 0-471-14056-2. Code, Image Processing. Chapters include: Advanced edge detection, Use of digital morphology, Advanced methods in grey-level segmentation, Texture, Skeletonization, Image Restoration, Wavelets, OCR, Symbol recognition, GA. Buy this book: Algorithms for Image Processing and Computer Vision BibRef

Parker, J.R.,
Practical Computer Vision Using C,
WileyOctober 1993. ISBN: 0-471-59262-5
HTML Version. Code, Computer Vision. Code, Image Processing, C. Buy this book: Practical Computer Vision Using C BibRef

Ritter, G.X.[Gerhard X.], and Wilson, J.N.[Joseph N.],
Handbook of Computer Vision Algorithms in Image Algebra,
CRC PressBoca Raton, FL, 1996. ISBN 0-8493-2636-2. Code, Image Processing.
WWW Version. BibRef

Umbaugh, S.E.[Scott E.],
Computer Vision and Image Processing: A Practical Approach Using CVIPtools,
New York: Prentice Hall1998. ISBN 0-13-264599-8, with a CD-ROM. Code, Image Processing. Application oriented. Analysis, Restoration, Enhancement, Compression. Buy this book: Computer Vision and Image Processing: A Practical Approach Using CVIPTools (BK/CD-ROM) BibRef

Jähne, B.[Bernd], Haussecker, H.W.[Horst W.], and Geissler, P., (eds.),
Handbook of Computer Vision and Applications. 1. Sensors and Imaging,
Academic PressSan Diego, CA, 1999. BibRef
And:
Handbook of Computer Vision and Applications. 2. Signal Processing and Pattern Recognition,
Academic PressSan Diego, CA, 1999. BibRef
And:
Handbook of Computer Vision and Applications. 3. Systems and Applications,
Academic PressSan Diego, CA, 1999. Three volumes and CD-ROM set, xxiii + 623 + xxiii + 942 + xlv + 894 pp., $995. ISBN 0-12-379770-5. Indexed under: BibRef HCVA99 Code, Computer Vision. Buy this book: Handbook Of Computer Vision And Applications 3 Vol Set And Cd-rom Set BibRef

Jähne, B.[Bernd], Haussecker, H.W.[Horst W.],
Computer Vision and Applications: A Guide for Students and Practitioners,
Academic PressApril 2000, 693 pp, ISBN: 978-0-12-379777-3. Code, Computer Vision.
WWW Version. A concise edition based on the 3 volume set above. The main parts parallel the volumes above. Buy this book: Computer Vision and Applications: A Guide for Students and Practitioners (With CD-ROM) BibRef

Nikolaidis, N.[Nikos], Pitas, I.[Ioannis],
3-D Image Processing Algorithms,
John Wiley& Sons, October 2000. ISBN: 0471377368. Analysis of 3-D data (volume filtering, features of 3-D objects, etc.) With the EIKONA3D software:
WWW Version. Code, Image Processing. Buy this book: 3-D Image Processing Algorithms BibRef

Whelan, P.F., and Molloy, D.,
Machine Vision Algorithms in Java: Techniques and Implementation,
SpringerLondon, October 2000. ISBN: 1-85233-218-2.
WWW Version. or
WWW Version. Code, Image Processing. Code, Image Processing, Java. Buy this book: Machine Vision Algorithms in Java: Techniques and Implementation BibRef

Ma, Y., Soatto, S., Kosecká, J., Sastry, S.S.,
An Invitation to 3-D Vision: From Images to Geometric Models,
Springer-Verlag2005 ISBN: 0-387-00893-4.
WWW Version. Code, Computer Vision. Buy this book: An Invitation to 3-D Vision BibRef

Paragios, N.[Nikos], Chen, Y.M.[Yun-Mei], Faugeras, O.D.[Olivier D.],
Handbook of Mathematical Methods in Computer Vision,
Springer2006, ISBN 978-0-387-26371-7 Indexed as: BibRef MMCV05 Code, Image Processing.
WWW Version. Discourse on the mathematical models used in computational vision. Topical areas include: image reconstruction, segmentation and object extraction, shape modeling and registration, motion analysis and tracking, and 3D from images, geometry and reconstruction. The book also includes a study of applications in medical image analysis. Buy this book: Handbook of Mathematical Models in Computer Vision BibRef

Paragios, N.[Nikos], Chen, Y.M.[Yun-Mei], and Faugeras, O.D.[Olivier D.], (Eds.)
Handbook of Mathematical Models in Computer Vision,
Springer2005. ISBN 0387263713
WWW Version. Code, Computer Vision. Variational Techniques, Boundary Extraction, Segmentation and Grouping, Shape Modeling and Registration. Buy this book: Handbook of Mathematical Models in Computer Vision BibRef

Pavlidis, T.,
Algorithms for Graphics and Image Processing,
Rockville MD: Computer Science Press1982. Survey, Algorithms. Algorithms, Survey. Code, Image Processing. The book has basic algorithms for many standard image processing tasks. Topics: Digitization, processing, segmentation, projection, data structures, binary images, contour filling, thinning, curve fitting, surface fitting, 2-D graphics, polygon clipping, 3-D graphics. BibRef

Stearns, S.D.[Samuel D.], David, R.A.[Ruth A.],
Signal Processing Algorithms in MATLAB,
Prentice Hall1996. ISBN 0-13-045154-1. Code, Signal Processing. Code, Image Processing, Matlab. BibRef
And:
Signal Processing Algorithms in Fortran and C,
Prentice Hall1993. Code, Signal Processing. BibRef
And: Code, Image Processing, C.
Signal Processing Algorithms,
Prentice Hall1988. BibRef

Lindley, C.A.,
Practical Image Processing in C,
WileyNew York, 1991. Source code included on floppy. Code, Image Processing. Code, Image Processing, C. BibRef

Svoboda, T.[Tomas], Kybic, J.[Jan], Hlavac, V.[Vaclav],
Image Processing, Analysis and and Machine Vision: A MATLAB Companion,
Cengage2008. ISBN-10: 0495295957. ISBN-13: 9780495295952 Code, Image Processing. Code, Image Processing, Matlab. Buy this book: Image Processing, Analysis & and Machine Vision - A MATLAB Companion BibRef

Pitas, I.[Ioannis],
Digital Image Processing Algorithms and Applications,
John Wiley& Sons, Inc. February 2000. ISBN: 0-471-37739-2. Multimedia material for the book:
WWW Version. Code, Image Processing. Buy this book: Digital Image Processing Algorithms and Applications BibRef

Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.,
Numerical Recipes in C: The Art of Scientific Computing,
Cambridge University Press1993 , ISBN 0521431085. Code, Numerical Algorithms. Code, Image Processing, C.
WWW Version. Buy this book: Numerical Recipes in C: The Art of Scientific Computing BibRef

Pratt, W.K.[William K.],
PIKS Foundation C Programmer's Guide,
Manning Publications1995. ISBN 0-13-172339-1. Guide for using the Programmer's Imaging Kernel System standard. Code, Image Processing. Code, Image Processing, C. Buy this book: Piks Foundation: A C Programmer's Guide BibRef

Kabir, I.[Ihtisham],
High Performance Computer Imaging,
Manning/ Prentice HallAugust 1996. ISBN 0-13-268301-6 (Initial reference gave: 1-884777-26-0). 378 pp. Code, Image Processing. Code, Image Processing, C. Includes a large selection of C code. Intended for the practical user who wants to implement computer imaging techniques. Details and a sample:
HTML Version. Buy this book: High Performance Computer Imaging BibRef

Klette, R.[Reinhard], Zamperoni, P.[Piero],
Handbook of Image Processing Operators,
John Wiley& Sons, 1996. ISBN 0-471-95642-2. Code, Image Processing. Code dealing with image processing defined as mappings of images onto images. This is a translation from the original German book. Buy this book: Handbook of Image Processing Operators BibRef

Russ, J.C.[John C.],
The Image Processing Handbook,
CRC PressBoca Raton, FL, Fifth Edition, 2007. ISBN: 9780849372544. Code, Image Processing.
WWW Version. Buy this book: The Image Processing Handbook, Fifth Edition (Image Processing Handbook) BibRef
Earlier: CRC PressBoca Raton, FL, Third Edition, 1999. ISBN 0-8493-2532-3. BibRef
And: IEEE_PressNew York, 1994, Second Edition. BibRef
And: CRC Press1995. ISBN 0-8493-2516-1. BibRef

Lyon, D.A.[Doublas A.],
Image Processing in Java,
Prentice Hall1999. ISBN 0-13-974577-7. Fundamentals and java code. Code, Image Processing. Code, Image Processing, Java. Buy this book: Image Processing in Java BibRef

Efford, N.[Nick],
Digital Image Processing: A Practical Introduction Using Java,
Addison Wesley2000. ISBN 0201596237. Code, Image Processing. Code, Image Processing, Java. Buy this book: Digital Image Processing: A Practical Introduction Using Java (With CD-ROM) BibRef

Rodrigues, L.H.[Lawrence H.],
Building Imaging Applications with Java(TM),
Addison Wesley2001. ISBN 0201700743. Code, Image Processing. Code, Image Processing, Java. Buy this book: Building Imaging Applications with Java(TM) Technology: Using AWT Imaging, Java 2D(TM), and Java(TM) Advanced Imaging (JAI) BibRef

Seul, M.[Michael], O'Gorman, L.[Lawrence], Sammon, M.J.[Michael J.],
Practical Algorithms for Image Analysis: Description, Examples, and Code,
Cambridge University2001. ISBN 0521660653.
WWW Version. Code, Image Processing. Buy this book: Practical Algorithms for Image Analysis: Descriptions, Examples, and Code BibRef

Gonzalez, R.C.[Rafael C.], Woods, R.E.[Richard E.], Eddins, S.L.[Steven L.],
Digital Image Processing Using MATLAB(R), 2nd Edition,
Gatesmark Publishing2009. ISBN: 9780982085400.
HTML Version. Buy this book: Digital Image Processing Using MATLAB, 2nd ed. Code, Image Processing. Code, Image Processing, Matlab. BibRef
Earlier:
Digital Image Processing Using MATLAB(R),
Prentice Hall2004 ISBN: 0-13-008519-7
HTML Version.
HTML Version. Buy this book: Digital Image Processing Using MATLAB BibRef

Blanchet, G.[Gerard], Charbit, M.[Maurice],
Digital Signal and Image Processing Using MATLAB(R),
ISTE Ltd2006. Code, Image Processing. Code, Image Processing, Matlab. ISBN: 1905209134. Buy this book: Digital Signal and Image Processing Using MATLAB (Digital Signal and Image Processing series) BibRef

Burger, W.[Wilhelm], and Burge, M.J.[Mark J.],
Digital Image Processing: An Algorithmic Approach Using Java,
Springer2007. ISBN 1846283795 and ISBN 3540309403. Code, Image Processing. Code, Image Processing, Java. Buy this book: Digital Image Processing: An Algorithmic Introduction using Java Or the German version: Buy this book: Digitale Bildverarbeitung: Eine Einführung mit Java und ImageJ (X.media.press) BibRef

Burger, W.[Wilhelm], Burge, M.J.[Mark J.],
Principles of Digital Image Processing: Core Algorithms,
Springer2009, ISBN: 978-1-84800-194-7
WWW Version. Supplemtary information:
WWW Version. Code, Image Processing. Code, Image Processing, Java. Second in the series. Color, comparing images, curve and corner, Fourier and Cosine transforms, Regions techniques. Buy this book: Principles of Digital Image Processing: Core Algorithms (Undergraduate Topics in Computer Science) BibRef

Burger, W.[Wilhelm], Burge, M.J.[Mark J.],
Principles of Digital Image Processing: Fundamental Techniques,
Springer2009, ISBN: 978-1-84800-190-9
WWW Version.
Third in the series. Edges, contours, Filters (linear, nonlinear), Image morphology, Image statistics, Image types and formats. Supplemtary information:
WWW Version. Code, Image Processing. Code, Image Processing, Java. Buy this book: Principles of Digital Image Processing: Fundamental Techniques (Undergraduate Topics in Computer Science) BibRef

Wang, M.Q.[Mei-Qing], Lai, C.H.[Choi-Hong],
A Concise Introduction to Image Processing using C++,
CRC PressNovember 2008, ISBN: 9781584888970 Code, Image Processing. Code, Image Processing, C++.
WWW Version. Buy this book: A Concise Introduction to Image Processing using C++ (Chapman & Hall/Crc Numerical Analysis and Scientific Computing)
BibRef

Qidwai, U.[Uvais], Chen, C.H.,
Digital Image Processing: An Algorithmic Approach with MATLAB,
CRC PressOctober 2009, ISBN: 9781420079500. Code, Image Processing. Code, Image Processing, Matlab.
WWW Version. Buy this book: Digital Image Processing: An Algorithmic Approach with MATLAB (Chapman & Hall/Crc Textbooks in Computing)
BibRef

Chaira, T.[Tamalika], Ray, A.K.[Ajoy Kumar],
Fuzzy Image Processing and Applications with MATLAB,
CRC PressNovember 2009, ISBN: 9781439807088. Code, Image Processing. Code, Image Processing, Matlab.
WWW Version. Buy this book: Fuzzy Image Processing and Applications with MATLAB
BibRef

Demirkaya, O.[Omer], Asyali, M.H.[Musa H.], Sahoo, P.K.[Prasanna K.],
Image Processing with MATLAB: Applications in Medicine and Biology,
CRC PressSeptember 2008, ISBN: 9780849392467. Code, Image Processing. Code, Image Processing, Matlab.
WWW Version. Buy this book: Image Processing with MATLAB: Applications in Medicine and Biology (MATLAB Examples)
BibRef

Min, J.[Jaesik], Powell, M.W.[Mark W.], Bowyer, K.W.[Kevin W.],
Automated Performance Evaluation of Range Image Segmentation Algorithms,
SMC-B(34), No. 1, February 2004, pp. 263-271.
IEEE Abstract.
BibRef
Earlier:
Automated Performance Evaluation of Range Image Segmentation,
WACV00(163-168).
IEEE Abstract.
Code, Segmenation Evaluation.
HTML Version. BibRef

OSGeo: Open Source Geospatial Foundation,
2009. Code, Geospatial. Code, GIS. Code, Open Source.
WWW Version. Data access, mapping, public geospatial data, GIS. See also LibTIFF: TIFF Library and Utilities.

Canty, M.J.[Morton J.],
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL,
Second Edition: CRC PressDecember 2009, ISBN: 9781420087130 Buy this book: Image Analysis, Classification, and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL, Second Edition First edition: BibRef CRC PressAugust, 2006, ISBN: 9780849372513
WWW Version. Code, Image Processing.
BibRef

Garris, M.D.,
Nist Form-Based Handprint Recognition System (Release 2.2),
NISTIRApril 2003.
HTML Version. Code, OCR. Standard reference form-based handprint recognition system for evaluating optical character recognition. BibRef

Gamera project,
Online2007.
WWW Version. Code, Document Analysis. A framework for the creation of structured document analysis applications by domain experts. BibRef

Dalitz, C.[Christoph], Karsten, T.[Thomas], Droettboom, M.[Michael], Fujinaga, I.[Ichiro], Pose, F.[Florian], Czerwinski, B.[Bastian],
Staff Line Removal Toolkit for Gamera,
Online2005-2007.
WWW Version. Code, Music Processing. BibRef

GOCR,
2002. Open Source OCR.
WWW Version. Code, OCR.

Google Tesseract-OCR,
1995 OCR originally developed at HP.
WWW Version. Code, OCR.

Funt, B., Ciurea, F., McCann, J.J.,
Retinex in Matlab,
JEI(13), No. 1, January 2004, pp. 48-57.
HTML Version. Code, Retinex. Code, Retinex, Matlab.
WWW Version. BibRef

Radar Tools,
2006.
WWW Version. Code, Radar. The Berlin group.

Mathematical Morphology,
OnlineAugust, 1998.
WWW Version. Code, Morphology. Code, Visualization. Khoros code for morphology. BibRef

Sarkar, S., and Boyer, K.L.,
Computing Perceptual Organization in Computer Vision,
World Scientific1994. (ISBN: 981-02-1832-X). 232pp. BibRef Book Code, Perceptual Grouping. Code:
HTML Version. Based on Sarkar's thesis. Derive a framework for perceptual organization at various levels. lower levels feed higher levels. Does not get to the recognition level. BibRef

Jacobs, D.W.,
Robust and Efficient Detection of Salient Convex Groups,
PAMI(18), No. 1, January 1996, pp. 23-37.
IEEE Abstract.
WWW Version. Code, Convex Grouping. Code:
WWW Version. BibRef
Earlier:
Robust and efficient detection of convex groups,
CVPR93(770-771).
IEEE Abstract. Groupings of line segments into convex objects. For finding m groups in n lines, the algorithm is (n^2)log(n)+nm BibRef

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PAMI(25), No. 6, June 2003, pp. 642-660.
IEEE Abstract.
Evaluation, Segmentation.
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Turk, G., Levoy, M.,
Zippered Polygon Meshes from Range Images,
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CVIU(89), No. 2-3, February-March 2003, pp. 197-225.
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IEEE DOI Link Code, Active Blobs.
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map3d: Interactive scientific visualization tool for bioengineering data,
2006. Code, 3-D Visualization.
HTML Version. Scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models.

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2006. Code, 3-D Segmentation.
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Hoover, A.[Adam], Goldgof, D.[Dmitry], Bowyer, K.W.[Kevin W.],
The Space Envelope: A Representation for 3D Scenes,
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WWW Version. Code, Space Envelope.
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Make3D,
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Lighting Sensitive Display,
ToG(23), No. 4, October 2004, pp. 963-979.
PDF Version. Code, Relighting.
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Iverson, L.A., Zucker, S.W.,
Logical/Linear Operators for Image Curves,
PAMI(17), No. 10, October 1995, pp. 982-996.
IEEE Abstract.
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HTML Version. Compared in: See also Robust Visual Method for Assessing the Relative Performance of Edge Detection Algorithms, A. BibRef

Smith, S.M.[Stephen M.], Brady, J.M.,
Susan: A New Approach to Low-Level Image-Processing,
IJCV(23), No. 1, May 1997, pp. 45-78.
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Baker, S.[Simon], Nayar, S.K.[Shree K.],
Global Measures of Coherence for Edge Detector Evaluation,
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IEEE Abstract. Code, Edge Detection.
WWW Version. For code and images:
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Rosin, P.L.[Paul L.], West, G.A.W.[Geoff A.W.],
Nonparametric Segmentation of Curves into Various Representations,
PAMI(17), No. 12, December 1995, pp. 1140-1153.
IEEE Abstract.
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Alvey88(259-263). BibRef
Earlier: A2, A1:
Multi-stage Combined Ellipse and Line Detection,
BMVC92(197-206).
PDF Version.
Segments into various components, lines, arcs (circular, elliptical, etc.). A fairly general complete algorithm. An extensive bibliography of earlier curve partitioning work. BibRef

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Non-Parametric Multi-Scale Curve Smoothing,
PRAI(8), 1994, pp. 1381-1406. BibRef
Earlier: SPIE(1964), April 1993, pp. 66-77 Code, Curve Smoothing. Code is available:
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Zingaretti, P.[Primo], Gasparroni, M.[Massimiliano], Vecci, L.[Lorenzo],
Fast Chain Coding of Region Boundaries,
PAMI(20), No. 4, April 1998, pp. 407-415.
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2007.
WWW Version. Code, Chain Code. Code, Chain Code, C.

Pilu, M.[Maurizio], Fitzgibbon, A.W., Fisher, R.B.,
Ellipse-Specific Direct Least-Square Fitting,
ICIP96(III: 599-602).
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Monga, O., Deriche, R., Malandain, G., and Cocquerez, J.P.,
Recursive Filtering and Edge Tracking: Two Primary Tools for 3D Edge Detection,
IVC(9), No. 4, August 1991, pp. 203-214.
WWW Version. Code, Edge Detection. BibRef
Earlier:
3D Edge Detection by Separable Recursive Filtering and Edge Closing,
ICPR90(I: 652-654).
IEEE DOI Link BibRef
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Recursive Filtering and Edge Closing: Two Primary Tools for 3D Edge Detection,
ECCV90(56-65).
Springer DOI Link For the code see:
WWW Version. See the above paper. See also Thin Nets and Crest Lines: Application to Satellite Data and Medical Images. BibRef

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January, 2006.
WWW Version. Code, Kalman Filter.

Welch, G.[Greg], and Bishop, G.[Gary],
An Introduction to the Kalman Filter,
TR95-041, University of North Carolina at Chapel Hill, Department of Computer Science, 1995.
WWW Version. Survey, Kalman Filter. Code, Kalman Filter. Tutorial on Kalman filter. All you want to know. BibRef

Simoncelli, E.P.[Eero P.], and Freeman, W.T.[William T.],
The Steerable Pyramid: A Flexible Architecture for Multi-Scale Derivative Computation,
ICIP95(III: 444-447).
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Steerable Filter. Code, Steerable Filter. tight frame, rotation-invariant filters.
HTML Version. And
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HTML Version. BibRef

Oram, D.,
Rectification for any epipolar geometry,
BMVC01(Session 7: Geometry &. Structure).
HTML Version.
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WWW Version. University of Manchester
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Section, Multiple Entries: 5.4.3.2 Vector Quantization Code Book Generation, Learning and Search Chapter Contents (Back)
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JPEG: Joint Photographic Experts Group,
Online2007.
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Code, Image Processing.
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Liu, D.Y., Tsai, C.W., Wu, J.L.,
A Java-Based MPEG-4 Like Video Codec,
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Code, Image Coding. Code, Image Coding, Java. BibRef

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Lotus Hill Institute,
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Khoral Research, Inc,
Software development. WWW Version.
Creators of Khoros which is now available from: AccuSoft,
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Code, Image Processing. Research Group, Company.

National Institute of Standards and Technology (NIST) Intelligent Systems Division,
NISTIR WWW Version.
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Earlier references: BibRef Journal of Research National Bureau of Standards,
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Software guide. WWW Version.
Code, Mathematical Software. Research Group, US Government. See also FERET Database, The. See also NIST Mugshot Identification Database. See also NIST ICE Iris Image Database. See also NIST Special Database 4, Fingerprint Database.

Robot Vision 2 Inc.,
Image processing. WWW Version.
Research Group, Company. Code, Image Analysis. Cross Platform software development and software for Image Processing and Robot Vision

Schuck, P.W.[Peter W.],
Tracking Vector Magnetograms with the Magnetic Induction Equation,
ApJ(683), 2008, pp. 1134-1152
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WWW Version. Code, Tracking. BibRef

Felzenszwalb, P.F.[Pedro F.], Huttenlocher, D.P.[Daniel P.],
Efficient Belief Propagation for Early Vision,
IJCV(70), No. 1, October 2006, pp. 41-54.
Springer DOI Link
PDF Version.
BibRef
Earlier: CVPR04(I: 261-268).
IEEE Abstract.
PDF Version. Code, Stereo. Code:
WWW Version. For stereo and reconstruction.
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Crandall, D.J.[David J.], Huttenlocher, D.P.[Daniel P.],
Composite Models of Objects and Scenes for Category Recognition,
CVPR07(1-8).
IEEE DOI Link
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Earlier:
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ECCV06(I: 16-29).
Springer DOI Link
Code, Object Recognition. Code:
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Crandall, D.J.[David J.], Felzenszwalb, P.F.[Pedro F.], Huttenlocher, D.P.[Daniel P.],
Spatial Priors for Part-Based Recognition Using Statistical Models,
CVPR05(I: 10-17).
IEEE DOI Link
PDF Version.
Code, Object Recognition. Code:
WWW Version. Find matches for the parts in an overall structure. BibRef

Rajwade, A.[Ajit], Banerjee, A.[Arunava], Rangarajan, A.[Anand],
Probability Density Estimation Using Isocontours and Isosurfaces: Applications to Information-Theoretic Image Registration,
PAMI(31), No. 3, March 2009, pp. 475-491.
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Code, Isocontour. BibRef
Earlier:
New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration,
CVPR06(II: 1769-1776).
IEEE DOI Link
Assume an image is a piecewise-continuous function, not a discrete set of pixels. Code is available.
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Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.P.W.,
elastix: A Toolbox for Intensity-Based Medical Image Registration,
MedImg(29), No. 1, January 2010, pp. 196-205.
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Lee, J.J.[John J.],
LIBPMK: A Pyramid Match Toolkit,
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WWW Version. Code, Matching. Code for: See also Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences. BibRef

Persoon, E., and Fu, K.S.,
Shape Discrimination Using Fourier Descriptors,
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Sclaroff, S.[Stan], and Pentland, A.P.,
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PAMI(17), No. 6, June 1995, pp. 545-561.
IEEE Abstract.
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And: Vismod-304, 1994.
HTML Version. and
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Komodakis, N.[Nikos], Tziritas, G.[Georgios], Paragios, N.[Nikos],
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WWW Version.
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Earlier:
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IEEE DOI Link
PDF Version.
Code, Alignment.
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Earlier: A1, A3, A2:
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Nonlinear programming techniques. Markov random fields; Linear programming; Primal-dual schema; Discrete optimization; Graph cuts BibRef

Murase, H.[Hiroshi], Nayar, S.K.[Shree K.], and Nene, S.A.[Sameer A.],
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HTML Version. Code, Active Appearance Model. A set of tools to build and play with Appearance Models and AAMs. See also University of Manchester, Medicine.

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WWW Version. Code, Active Appearance Model. Code, Open Source.

Stegmann, M.B.[Mikkel B.],
Active Appearance Models,
Online2007.
WWW Version. Code, Active Appearance Model. Dataset, Active Appearance Model. AAM code and information. See also Technical University of Denmark. BibRef

Lowe, D.G.[David G.],
Distinctive Image Features from Scale-Invariant Keypoints,
IJCV(60), No. 2, November 2004, pp. 91-110.
WWW Version.
Code, SIFT. BibRef
Earlier:
Object Recognition from Local Scale-Invariant Features,
ICCV99(1150-1157).
IEEE DOI Link New class of features, similar to neurons. Extract features that can be used in matching. SIFT -- Scale Invariant Feature Code is available:
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Gary, K., Ibanez, L., Aylward, S., Gobbi, D., Blake, M.B., Cleary, K.,
IGSTK: an open source software toolkit for image-guided surgery,
Computer(39), No. 4, April 2006, pp. 46-53.
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Code, Surgery. BibRef

Mustra, M., Grgic, M., Delac, K.,
Efficient presentation of DICOM mammography images using Matlab,
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Code, Mammography. BibRef

Ijaz, U.Z., Chaudhary, S.U., Don, M.S., Kim, K.Y.,
Computational strategies for protein quantitation in 2D electrophoresis gel image processor for Matlab,
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Xu, L., Jackowski, M., Goshtasby, A., Roseman, D., Bines, S., Yu, C., Dhawan, A., Huntley, A.,
Segmentation skin cancer images,
IVC(17), No. 1, January 1999, pp. 65-74.
WWW Version. Code, Segmentation. Software describe here is available from:
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Xu, G.[Gang], Sugimoto, N.[Noriko],
Linear Algorithm for Motion from Three Weak Perspective Images Using Euler Angles,
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IEEE Abstract.
WWW Version. Code, Motion. Code is available:
HTML Version. Determine the rotations and structure. Uses epipolar geometry computations from: See also Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach. But see results in: See also Motion Estimation With More Than Two Frames. BibRef

Toyama, K.[Kentaro], Hager, G.D.[Gregory D.],
Incremental Focus of Attention for Robust Vision-Based Tracking,
IJCV(35), No. 1, November 1999, pp. 45-63.
WWW Version. BibRef
Earlier:
Incremental Focus of Attention for Robust Visual Tracking,
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IEEE Abstract.
WWW Version. Tracking.
HTML Version. And
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Earlier:
Tracker Fusion for Robustness in Visual Feature Tracking,
SPIE(2569), pp. 38-49. Photonics East, October 1995.
Postscript Version. Code, Tracking. Code:
WWW Version. BibRef

Sinha, S.N.[Sudipta N.],
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Online2007. Code, Tracking. C++ Code for Kanade-Lucas-Tomasi feature tracker. See also Shape and Motion from Image Streams: A Factorization Method Part 3 - Detection and Tracking of Point Features. See also KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker. BibRef

Torresani, L.[Lorenzo], Hertzmann, A.[Aaron],
Automatic Non-rigid 3D Modeling from Video,
ECCV04(Vol II: 299-312).
WWW Version.
Given initial region, track and model non-rigid shape. Movie:
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Adam, A.[Amit],
Fragments Tracker,
Online2008.
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Zimmermann, K.[Karel], Matas, J.G.[Jirí G.], Svoboda, T.[Thomáš],
Tracking by an Optimal Sequence of Linear Predictors,
PAMI(31), No. 4, April 2009, pp. 677-692.
IEEE DOI Link
Code, Tracking. Dataset, Tracking. BibRef
Earlier: A1, A3, A2:
Simultaneous learning of motion and appearance,
MLMotion08(xx-yy).
BibRef
Earlier: A1, A3, A2:
Adaptive Parameter Optimization for Real-time Tracking,
NRTL07(1-8).
IEEE DOI Link
BibRef
Earlier: A1, A3, A2:
Multiview 3D Tracking with an Incrementally Constructed 3D Model,
3DPVT06(488-495).
IEEE DOI Link
Learning approach to tracking. Estimation of the pose given the pose of the previous frame. Matlab implementation available.
WWW Version. BibRef

Siebel, N.T.[Nils T],
Design and Implementation of People Tracking Algorithms for Visual Surveillance Applications,
Ph.D.Thesis, March 2003, Department of Computer Science, The University of Reading, Reading, UK.
PDF Version. Code, Tracking.
WWW Version. BibRef

Baseline Algorithm and Performance for Gait Based Human ID Challenge Problem,
2004, USF.
WWW Version. Dataset, Gait. Code, Gait.

CMU Graphics Lab Motion Capture Database,
2004.
WWW Version. Dataset, Motion Capture. Code, Motion Capture. 2000+ examples of motion capture data. Includes some software.

Panorama Tools,
2006.
WWW Version. Code, Image Stitching. Mosaic Generation software.

XuvTools - eXtend yoUr View Toolkit,
2008
HTML Version. Code, Image Stitching. Mosaic generation software and High Dynamic Range software.

Nomura, Y.[Yoshikuni], Zhang, L., Nayar, S.K.[Shree K.],
Scene Collages and Flexible Camera Arrays,
ConferenceEurographics Symposium on Rendering, Jun, 2007.
PDF Version.
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Super-Resolution Code,
Online2007. Code, Super-Resolution.
HTML Version. Matlab/C code. See also Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?. BibRef

Manders, C.[Corey], Farbiz, F.[Farzam], Mann, S.[Steve],
A Compression Method for Arbitrary Precision Floating-Point Images,
ICIP07(IV: 165-168).
IEEE DOI Link
Code, Image Compression.
HTML Version. Reorganize the data then use JPEG or other compression. For high dynamic range images. BibRef

Birchfield, S.T.[Stan T.],
KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker,
Online1997. Code, Tracking.
WWW Version. See also GPU_KLT: A GPU-based Implementation of the Kanade-Lucas-Tomasi Feature Tracker. BibRef

Jacobs, D.W.[David W.],
Linear Fitting with Missing Data for Structure-from-Motion,
CVIU(82), No. 1, April 2001, pp. 57-81.
WWW Version.
Code, Surface Fitting. Code:
WWW Version. BibRef
Earlier:
Linear Fitting with Missing Data: Applications to Structure from Motion and to Characterizing Intensity Images,
CVPR97(206-212).
IEEE Abstract.
WWW Version.
Problems reduce to fitting surface to data. BibRef

Barron, J.L., Fleet, D.J., and Beauchemin, S.S.,
Performance of Optical Flow Techniques,
IJCV(12), No. 1, February 1994, pp. 43-77.
Springer DOI Link
HTML Version.
WWW Version. BibRef
And: Add: Burkitt, T.A., CVPR92(236-242).
IEEE Abstract. Code, Optic Flow. Survey, Optic Flow. Survey of the field and a comparison of a variety of techniques. Compares quality of results, not execution time. Compares: Lucas/Kanade ( See also Generalized Image Matching by the Method of Differences. ), Fleet/Jepson ( See also Hierarchial Construction of Orientation and Velocity Selective Filters. ), Uras ( See also Computational Approach to Motion Perception, A. ), Nagel ( See also On a Constraint Equation for the Estimation of Displacement Rates in Image Sequences. ), Anandan ( See also Computational Framework and an Algorithm for the Measurement of Visual Motion, A. ), Horn/Shunck ( See also Determining Optical Flow. ), Singh ( See also Image-Flow Computation: An Estimation-Theoretic Framework and a Unified Perspective. ). Code for all of these is available from:
WWW Version. BibRef

McCane, B.[Brendan],
Optic Flow Evaluation,
OnlineMarch 2007.
WWW Version. Code, Optic Flow. BibRef

Black, M.J., Anandan, P.,
The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow-Fields,
CVIU(63), No. 1, January 1996, pp. 75-104.
WWW Version.
HTML Version. Code:
HTML Version. Code, Optic Flow. BibRef
Earlier:
A Framework for the Robust Estimation of Optical Flow,
ICCV93(231-236).
IEEE DOI Link BibRef
Earlier:
Robust Dynamic Motion Estimation Over Time,
CVPR91(296-302).
IEEE Abstract.
HTML Version. BibRef
And:
The Robust Estimation of Multiple Motions: Affine and Piecewise-Smooth Flow-Fields,
TR Xerox PARC, December 1993. Motion, Many Frames. Incremental tracking system using multiple resolutions. BibRef

Camus, T.A.,
Real-Time Quantized Optical Flow,
RealTimeImg(3), 1997, pp. 71-86. BibRef
Earlier: CAMP95(xx). Implementation of algorithm. Code, Optic Flow.
WWW Version. BibRef

Georgescu, B.[Bogdan],
HEIV based estimation,
OnlineSeptember, 2002. Code, HEIV.
WWW Version. Code related to above paper. See also Estimation of Nonlinear Errors-in-Variables Models for Computer Vision Applications. BibRef

Presto-Box: Pattern REcognition Scilab TOolBOX,
2001
HTML Version. Code, Pattern Recognition. Routines for students to experiment with basic pattern recognition principles.

PRTools: The Matlab Toolbox for Pattern Recognition,
2004.
WWW Version. Code, Pattern Recognition. Matlab package for PR Implementation based on the book: See also Classification, parameter estimation and state estimation: An engineering approach using Matlab.

MultiSpec: A Freeware Multispectral Image Data Analysis System,
2007.
WWW Version. Code, Pattern Recognition. Purdue package for analyzing multispectral and hyperspectral data. See also Purdue University.

Carreira-Perpiñán, M.Á.[Miguel Á.],
Mode-Finding for Mixtures of Gaussian Distributions,
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IEEE Abstract.
WWW Version.
Matlab implementation and TR with mathematical details:
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Chang, C.C., Lin, C.J.,
LIBSVM: a library for support vector machines,
Online2001.
WWW Version. Code, Support Vector Machines. BibRef

LIBSVMTL: a Support Vector Machine Template Library,
Online2001.
HTML Version. Code, Support Vector Machines. Based on LIBSVM above. BibRef

Torch: Machine-Learning Library,
2004.
WWW Version. Code, Learning. Open source learning library.

Pandya, A.S.[Abhijit S.], Macy, R.B.[Robert B.],
Pattern Recognition with Neural Networks in C++,
CRC PressBoca Raton, FL. 1996. Code, Neural Networks. ISBN 0-8493-9462-7. Complete code for the various algorithms. BibRef

Qin, A.K., Suganthan, P.N.,
Enhanced neural gas network for prototype-based clustering,
PR(38), No. 8, August 2005, pp. 1275-1288.
WWW Version.
Code, Neural Networks. BibRef
Earlier:
Kernel neural gas algorithms with application to cluster analysis,
ICPR04(IV: 617-620).
IEEE DOI Link
Code available:
WWW Version. BibRef

Beveridge, J.R.[J. Ross], Bolme, D.S.[David S.], Draper, B.A.[Bruce A.], Teixeira, M.[Marcio],
The CSU Face Identification Evaluation System: Its purpose, features, and structure,
MVA(16), No. 2, February 2005, pp. 128-138.
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Evaluation, Faces. BibRef
Earlier: A2, A1, A4, A3: CVS03(304 ff).
HTML Version.

HTML Version. Code, Face Recognition. The four algorithms provided are principle components analysis (PCA), a.k.a eigenfaces ( See also Eigenfaces for Recognition. ), a combined principle components analysis and linear discriminant analysis algorithm (PCA + LDA) ( See also Discriminant Analysis of Principal Components for Face Recognition. ), an intrapersonal/extrapersonal image difference classifier (IIDC), ( See also Bayesian similarity measure for deformable image matching, A. ) and an elastic bunch graph matching (EBGM) algorithm ( See also Face Recognition by Elastic Bunch Graph Matching. ) The PCA + LDA, IIDC, and EBGM algorithms are based upon algorithms used in the FERET study ( See also FERET Evaluation Methodology for Face-Recognition Algorithms, The. ). BibRef

Face Recogniton Home Page,
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WWW Version. Code, Face Recognition. Dataset, Faces. Listing of research groups, databases, and vendors. BibRef

Face Detection Home Page,
Online2007.
WWW Version. Code, Face Detection. Dataset, Faces. Listing of research groups, databases, and vendors. BibRef

La Cascia, M.[Marco], Sclaroff, S.[Stan], Athitsos, V.[Vassilis],
Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Textured-Mapped 3D Models,
PAMI(22), No. 4, April 2000, pp. 322-336.
IEEE Abstract.
WWW Version.
PDF Version.
Code, Head Tracking.
HTML Version. Model the head as a texture mapped cylinder. See also Skin Color-Based Video Segmentation under Time-Varying Illumination. BibRef

openEyes,
2006.
WWW Version. Code, Eye Tracking. Open source code for eye tracking. See also Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches.

Sidenbladh, H.[Hedvig], Black, M.J.[Michael J.],
Learning the Statistics of People in Images and Video,
IJCV(54), No. 1-3, August 2003, pp. 183-209.
WWW Version.

PDF Version. Software for Matlab: Code, Tracking.
WWW Version. BibRef
Earlier:
Learning Image Statistics for Bayesian Tracking,
ICCV01(II: 709-716).
IEEE DOI Link
BibRef

de la Torre, F.[Fernando], Black, M.J.[Michael J.],
A Framework for Robust Subspace Learning,
IJCV(54), No. 1-3, August 2003, pp. 117-142.
WWW Version.
PDF Version.
Software for Matlab:
WWW Version. Code, PCA. BibRef

Venkatesh, S., Rosin, P.L.,
Dynamic Threshold Determination by Local and Global Edge Evaluation,
GMIP(57), No. 2, March 1995, pp. 146-160. BibRef
Earlier: SPIE(1964), 1993, pp. 40-50. Code, Segmentation. The code is available on the vision list archive:
WWW Version. BibRef

Comaniciu, D.[Dorin], Meer, P.[Peter],
Robust Analysis of Feature Spaces: Color Image Segmentation,
CVPR97(750-755).
IEEE Abstract.
WWW Version.
Code, Segmentation. Code, Segmentation, C++. For the C++ code:
HTML Version. Color quantization for segmentation. Map into another feature space. BibRef

Cour, T., Yu, S., and Shi, J.,
Normalized cut image segmenation software,
Online2006.
WWW Version. Code, Segmentation. Code, Segmentation, C. Matlab Code for segmentation and clustering. C code for segmentation. See also Normalized Cuts and Image Segmentation. BibRef

Arbelaez, P.[Pablo], Fowlkes, C.C.[Charless C.], and Martin, D.R.[David R.],
The Berkeley Segmentation Dataset and Benchmark,
Online2007. Dataset, Segmentation. Code, Segmentation.
WWW Version. The updated code and data for the earlier paper. See also Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics, A. BibRef

qsnake_demo,
2007. Code, Snakes.
HTML Version. Basic tool to play with snakes (active contour models).

Xu, C.Y.[Chen-Yang], Prince, J.L.[Jerry L.],
Generalized gradient vector flow external forces for active contours,
SP(71), No. 2, 15 December 1998, pp. 131-139. BibRef
Earlier:
Gradient Vector Flow: A New External Force for Snakes,
CVPR97(66-71).
IEEE Abstract.
WWW Version.
Code, Snakes. Code:
HTML Version. BibRef

Shor, R.[Ronen],
Intellegent Scissors: Interactive tool for image segmentation,
Online2008.
HTML Version. Code, Segmentation. Implementation of See also Interactive Segmentation with Intelligent Scissors. BibRef

Sumengen, B.[Baris], Manjunath, B.S.,
Graph Partitioning Active Contours (GPAC) for Image Segmentation,
PAMI(28), No. 4, April 2006, pp. 509-521.
IEEE DOI Link
Code, Segmentation. Code available
WWW Version. BibRef

Boykov, Y.Y.[Yuri Y.], Kolmogorov, V.[Vladimir],
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision,
PAMI(26), No. 9, September 2004, pp. 1124-1137.
IEEE Abstract.
BibRef
Earlier: EMMCVPR01(359-374).
Springer DOI Link
Code, Segmentation. BibRef
Earlier:
Computing geodesics and minimal surfaces via graph cuts,
ICCV03(26-33).
IEEE DOI Link
Combine geodesic active contours with graph cuts. See also Exact Maximum a Posterori Estimation for Binary Images. Code is available:
WWW Version. Code, Energy Minimization. BibRef

Mishra, A.[Ajay], Aloimonos, Y.[Yiannis], Fah, C.L.[Cheong Loong],
Code: Active Segmentation With Fixation,
Online2010. Code, Segmentation. Code, Snakes.
HTML Version. Code for ICCV 2009 paper. BibRef

Sumengen, B.[Baris],
Matlab toolbox for Level Set Methods,
Online2008.
HTML Version. Code, Segmentation. Code, Segmentation, Matlab. The code follows Osher and Fedkiw book. BibRef

Fan, D.,
Level-set image segmenation software,
Online2002.
WWW Version. Code, Segmentation. BibRef

Felzenszwalb, P.F.[Pedro F.], Huttenlocher, D.P.[Daniel P.],
Efficient Graph-Based Image Segmentation,
IJCV(59), No. 2, September 2004, pp. 167-181.
WWW Version.
PDF Version. Code, Segmentation. And code:
WWW Version.
BibRef

Edison: Edge Detection and Image SegmentatiON system,
Online2003.
HTML Version. Code, Segmentation. Code, Edge Detection. See also Mean Shift: A Robust Approach Toward Feature Space Analysis. BibRef

Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.,
Shape from Shading: A Survey,
PAMI(21), No. 8, August 1999, pp. 690-706.
IEEE Abstract.
WWW Version. Survey, Shape from Shading. Minimization: See also Estimation of Illuminant Direction, Albedo, and Shape from Shading. See also Shape from Shading with a Linear Triangular Element Surface Model. Propagation: See also Simple Algorithm for Shape for Shading, A. Local: See also Improved Methods of Estimating Shape from Shading Using the Light Source Coordinate System. Linear: See also Shape Information from Shading: A Theory about Human Perception. (Would See also On the Extraction of Shape Information from Shading. be better reference?) See also Shape From Shading Using Linear-Approximation. (The text says 1992, but that is the conference reference) Code, Shape from Shading.
WWW Version. BibRef

Tsai, P.S., Shah, M.,
Shape From Shading Using Linear-Approximation,
IVC(12), No. 8, October 1994, pp. 487-498.
WWW Version. Code, Shape from Shading.
HTML Version. BibRef
Earlier:
A Fast Linear Shape from Shading,
CVPR92(734-736).
IEEE Abstract. BibRef
And: Univ. of Central FloridaTR. Linear Approach. Short C program (25 lines) that converges in 2 interations. BibRef

Gu, J., Tu, C., Ramamoorthi, R., Belhumeur, P.N., Matusik, W., and Nayar, S.K.,
Time-varying Surface Appearance: Acquisition, Modeling, and Rendering,
ToG(25), July 2006.
PDF Version. Code, Surface Appearance.
WWW Version. BibRef

Watanabe, M., Nayar, S.K.,
Rational Filters for Passive Depth from Defocus,
IJCV(27), No. 3, May 1998, pp. 203-225.
WWW Version.
PDF Version.

WWW Version. Code, Depth from Focus. BibRef

Favaro, P.[Paolo], Soatto, S.[Stefano],
3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur,
Springer2007, ISBN 978-1-84628-176-1.
WWW Version. Code, Motion Blur. For implementations of relevant algorithms, test data and demos:
WWW Version. BibRef

Scharstein, D.[Daniel], Szeliski, R.S.[Richard S.],
Stereo Matching With Nonlinear Diffusion,
IJCV(28), No. 2, June-July 1998, pp. 155-174.
WWW Version.
BibRef
Earlier: CVPR96(343-350).
IEEE Abstract.
WWW Version. BibRef
And: CornellComputer Science, TR96-1575, March 1996. Code, Stereo. Code:
HTML Version. Point matching using Sum of Squared Differences (SSD). BibRef

Lucas, B.D., and Kanade, T.,
An Iterative Image Registration Technique with an Application to Stereo Vision,
DARPA81(121-130).
HTML Version. BibRef
And: IJCAI81(674-679).
HTML Version. Code, Registration.
WWW Version. Another version in Matlab.
WWW Version. Uses differences in intensity between the two images and the local gradient of one image (both?) to compute the shift. A registration problem, but very applicable to stereo. For more generalization: See also Shape and Motion from Image Streams: A Factorization Method Part 3 - Detection and Tracking of Point Features. BibRef

Baker, S.[Simon], Matthews, I.[Iain],
Lucas-Kanade 20 Years On: A Unifying Framework,
IJCV(56), No. 3, February-March 2004, pp. 221-255.
WWW Version.
BibRef
And:
Lucas-Kanade 20 Years On: A Unifying Framework: Part 1,
CMU-RI-TR-02-16, July 2002.
WWW Version.
BibRef
And:
Lucas-Kanade 20 Years On,
CMU-RI2006, Project Description.
HTML Version. Code, Tracking. Matlab code is available. See also Generalized Image Matching by the Method of Differences. See also Iterative Image Registration Technique with an Application to Stereo Vision, An. BibRef

Ogale, A.S.[Abhijit S.], Aloimonos, Y.[Yiannis],
Shape and the Stereo Correspondence Problem,
IJCV(65), No. 3, December 2005, pp. 147-162.
Springer DOI Link or:
PDF Version.
Code, Stereo. BibRef
Earlier:
Robust contrast invariant stereo correspondence,
CRA05(xx-yy).
PDF Version. BibRef
The influence of shape on image correspondence,
3DPVT04(945-952).
IEEE Abstract.
BibRef
And:
Stereo Correspondence with Slanted Surfaces: Critical Implications of Horizontal Slant,
CVPR04(I: 568-573).
IEEE Abstract. Or:
PDF Version.
Related code is also available:
HTML Version. BibRef

Scharstein, D.[Daniel], Szeliski, R.S.[Richard S.],
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms,
IJCV(47), No. 1-3, April-June 2002, pp. 7-42.
WWW Version.
Code, Stereo. Dataset, Stereo. The data sets and code are also available:
WWW Version. BibRef

SRI Stereo Engine,
2007
WWW Version. Code, Stereo. Efficient implementation of area correlation stereo.

Real Time Dense Stereo,
2007
WWW Version. Code, Stereo. C++ library for real-time disparity estimation. It computes dense stereo matching from 2 or 3 images as well as 3D scene reconstruction.

Kolmogorov, V.[Vladimir], Zabih, R.[Ramin],
Multi-camera Scene Reconstruction via Graph Cuts,
ECCV02(III: 82 ff.). Award, ECCV.
HTML Version.
BibRef
Earlier:
Computing Visual Correspondence with Occlusions via Graph Cuts,
ICCV01(II: 508-515).
IEEE DOI Link
Handle occlusions in correspondence. code is available:
WWW Version. Code, Stereo. BibRef

Snavely, N.[Noah],
Bundler: Structure from Motion for Unordered Image Collections,
OnlineMay 2009. Code, Structure from Motion.
WWW Version.
BibRef

Cryer, J.E., Tsai, P.S., and Shah, M.,
Integration of Shape from Shading and Stereo,
PR(28), No. 7, July 1995, pp. 1033-1043.
WWW Version. Code, Shape from Shading.
HTML Version. BibRef
Earlier:
Integration of Shape from X Modules: Combining Stereo and Shading,
CVPR93(720-721).
IEEE Abstract. Related SfS analysis: See also Analysis of Shape from Shading Techniques. BibRef

Gutierrez, J.A.[José A.], Armstrong, B.S.R.[Brian S.R.],
Precision Landmark Location for Machine Vision and Photogrammetry: Finding and Achieving the Maximum Possible Accuracy,
Springer2008, ISBN: 978-1-84628-912-5.
WWW Version. Code, Landmarks. Techniques to achieve optimal results. Buy this book: Precision Landmark Location for Machine Vision and Photogrammetry: Finding and Achieving the Maximum Possible Accuracy BibRef

Franco, J.S., Boyer, E.,
Exact polyhedral visual hulls,
BMVC03(xx-yy).
HTML Version.
Code, Convex Hull.
WWW Version. BibRef

Felzenszwalb, P.F.[Pedro F.], Huttenlocher, D.P.[Daniel P.],
Distance Transforms of Sampled Functions,
Cornell2004, Computing and Information Science TR2004-1963. Code, Distance Transform.
WWW Version. BibRef

Total found: 224
For more information on the topics, contact information, etc. see the annotated Computer Vision Bibliography or the Complete Conference Listing for Computer Vision and Image Analysis

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