• OpenCV Change Logs

OpenCV Change Logs

Change logs from OpenCV's official releases -- what is new in the new release

2.3.1

(August, 2011)

Android port

• OpenCV Java bindings for Android platform are released in Beta 2 quality. A lot of work is done to make them more stable and easier to use. Currently Java API has about 700 different OpenCV functions and covers 8 OpenCV modules including full port of features2d. See OpenCV for Android release notes for detailed information about Android-specific changes made for this release.

  And follow the instructions from Android page for getting started with OpenCV for Android.

Other New Functionality and Features

• Retina module has been contributed by Alexandre Benoit (in opencv_contrib module). See the new retina sample and https://sites.google.com/site/benoitalexandrevision/.

• Support for Ximea cameras (http://www.ximea.com/) in HighGUI has been contributed by Ximea developers.

• Planar subdivisions construction (Delaunay triangulation and Voronoi tesselation) have been ported to C++. See the new delaunay2.cpp sample.
• Several new Python samples have been added.
• FLANN in OpenCV has been upgraded to v1.6. Also, added Python bindings for FLANN.
• We now support the latest FFMPEG (0.8.x) that features multi-threaded decoding. Reading videos in OpenCV has never been that fast.

Documentation

• Quite a few new tutorials have been added. Check http://opencv.itseez.com/trunk for the up-to-date documentation.

Optimization

• Performance of the sparse Lucas-Kanade optical flow has been greatly improved. On 4-core machine it is now 9x faster than the previous version.

Bug Fixes

• Over 100 issues have been resolved since 2.3 release. Most of the issues (closed and still open) are listed at https://code.ros.org/trac/opencv/report/6.

Known Problems/Limitations

• TBD

2.3

(July, 2011)

Modifications and Improvements since 2.3rc

• A few more bugs reported in the OpenCV bug tracker have been fixed.
• Documentation has been improved a lot! The new reference manual combines information for C++ and C interfaces,
  • the OpenCV 1.x-style Python bindings and the new C++-style Python bindings. It has also been thoroughly checked for grammar, style and completeness. Besides, there are new and updated tutorials.

    The up-to-date online documentation is available at http://opencv.itseez.com.

• [Windows] The new binary package includes various pre-compiled libs:

  • https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.3/ Unfortunately, it's not a full-scale installation package, but simply a self-extracting archive with a readme.txt supplied. The installation package is probably to come in the next version.

• [Windows] VS2005 should build OpenCV 2.3 out of the box, including DirectShow support.

• [Windows] ffmpeg bindings are now available for all Windows users via compiler- and configuration- and
  • version-independent opencv_ffmpeg.dll (for 32-bit compilers) and opencv_ffmpeg_64.dll (for 64-bit compilers).

2.3rc

(June, 2011)

General Modifications and Improvements

• Buildbot-based Continuous Integration system is now continuously testing OpenCV snapshots. The status is available at http://buildbot.itseez.com

• OpenCV switched to Google Test (http://code.google.com/p/googletest/) engine for regression and correctness tests. Each module now has test subdirectory with the tests.

New Functionality, Features

• Many functions and methods now take InputArray/OutputArray instead of "cv::Mat" references. It retains compatibility with the existing code and yet brings more natural support for STL vectors and potentially other "foreign" data structures to OpenCV. See http://opencv.itseez.com/modules/core/doc/intro.html#inputarray-and-outputarray for details.

• core:
  • LAPACK is not used by OpenCV anymore. The change decreased the library footprint and the compile time. We now use our own implementation of Jacobi SVD. SVD performance on small matrices (2x2 to 10x10) has been greatly improved; on larger matrices it is still pretty good. SVD accuracy on poorly-conditioned matrices has also been improved.
  • Arithmetic operations now support mixed-type operands and arbitrary number of channels.
• features2d:
  • Completely new patent-free BRIEF and ORB feature descriptors have been added.
  • Very fast LSH matcher for BRIEF and ORB descriptors will be added in 2.3.1.
• calib3d:

  • A new calibration pattern, "circles grid" (), has been added. See findCirclesGrid() function and the updated calibration.cpp sample. With the new pattern calibration accuracy is usually much higher.

• highgui:
  • [Windows] videoInput is now a part of highgui. If there are any problems with compiling highgui, set "WITH_VIDEOINPUT=OFF" in CMake.
• stitching:

  • opencv_stitching is a beta version of new application that makes a panorama out of a set of photos taken from the same point.

• python:
  • Now there are 2 extension modules: cv and cv2. cv2 includes wrappers for OpenCV 2.x functionality. opencv/samples/python2 contain a few samples demonstrating cv2 in use.
• contrib:

  • A new experimental variational stereo correspondence algorithm StereoVar has been added.

• gpu:
  • the module now requires CUDA 4.0 or later; Many improvements and bug fixes have been made.

Android port

• With support from NVidia, OpenCV Android port (which is actually not a separate branch of OpenCV, it's the same code tree with additional build scripts) has been greatly improved, a few demos developed. Camera support has been added as well. See http://opencv.willowgarage.com/wiki/Android for details.

Documentation

• OpenCV documentation is now written in ReStructured Text and built using Sphinx (http://sphinx.pocoo.org).

• It's not a single reference manual now, it's 4 reference manuals (OpenCV 2.x C++ API, OpenCV 2.x Python API, OpenCV 1.x C API, OpenCV 1.x Python API), the emerging user guide and a set of tutorials for beginners.
• Style and grammar of the main reference manual (OpenCV 2.x C++ API) have been thoroughly checked and fixed.

• Online up-to-date version of the manual is available at http://opencv.itseez.com

Samples

• Several samples using the new Python bindings (cv2 module) have been added: https://code.ros.org/svn/opencv/branches/2.3/opencv/samples/python2

Optimization

• Several ML algorithms have been threaded using TBB.

Bug Fixes

• Over 250 issues have been resolved. Most of the issues (closed and still open) are listed at https://code.ros.org/trac/opencv/report/6.

Known Problems/Limitations

• Documentation (especially on the new Python bindings) is still being updated. Watch opencv.itseez.com for updates.

• Android port does not provide Java interface for OpenCV. It is going to be added to 2.3 branch in a few weeks.

• The list of the other open bugs can be found at http://code.ros.org/trac/opencv/report/1.

2.2

(December, 2010)

General Modifications and Improvements

• The library has been reorganized. Instead of cxcore, cv, cvaux, highgui and ml we now have several smaller modules:
  • opencv_core - core functionality (basic structures, arithmetics and linear algebra, dft, XML and YAML I/O ...).

  • opencv_imgproc - image processing (filter, GaussianBlur, erode, dilate, resize, remap, cvtColor, calcHist etc.)

  • opencv_highgui - GUI and image & video I/O

  • opencv_ml - statistical machine learning models (SVM, Decision Trees, Boosting etc.)
  • opencv_features2d - 2D feature detectors and descriptors (SURF, FAST etc.,
    • including the new feature detectors-descriptor-matcher framework)
  • opencv_video - motion analysis and object tracking (optical flow, motion templates, background subtraction)

  • opencv_objdetect - object detection in images (Haar & LBP face detectors, HOG people detector etc.)

  • opencv_calib3d - camera calibration, stereo correspondence and elements of 3D data processing
  • opencv_flann - the Fast Library for Approximate Nearest Neighbors (FLANN 1.5) and the OpenCV wrappers
  • opencv_contrib - contributed code that is not mature enough
  • opencv_legacy - obsolete code, preserved for backward compatibility
  • opencv_gpu - acceleration of some OpenCV functionality using CUDA (relatively unstable, yet very actively developed part of OpenCV)
• If you detected OpenCV and configured your make scripts using CMake or pkg-config tool, your code will likely build fine without any changes. Otherwise, you will need to modify linker parameters (change the library names) and update the include paths.

• It is still possible to use #include <cv.h> etc. but the recommended notation is:

  • #include "opencv2/imgproc/imgproc.hpp"
  • ..

• Please, check the new C and C++ samples (https://code.ros.org/svn/opencv/trunk/opencv/samples), which now include the new-style headers.

• The new-style wrappers now cover much more of OpenCV 2.x API. The documentation and samples are to be added later. You will need numpy in order to use the extra added functionality.
  • SWIG-based Python wrappers are not included anymore.

• OpenCV can now be built for Android (GSoC 2010 project), thanks to Ethan Rublee; and there are some samples too. Please, check http://opencv.willowgarage.com/wiki/Android

• The completely new opencv_gpu acceleration module has been created with support by NVidia. See below for details.

New Functionality, Features

• core:

  • The new cv::Matx<T, m, n> type for fixed-type fixed-size matrices has been added. Vec<T, n> is now derived from Matx<T, n, 1>. The class can be used for very small matrices, where cv::Mat use implies too much overhead. The operators to convert Matx to Mat and backwards are available.

  • cv::Mat and cv::MatND are made the same type: typedef cv::Mat cv::MatND. Note that many functions do not check the matrix dimensionality yet, so be careful when processing 3-, 4- ... dimensional matrices using OpenCV.
  • Experimental support for Eigen 2.x/3.x is added (WITH_EIGEN2 option in CMake). Again, there are convertors from Eigen2 matrices to cv::Mat and backwards. See modules/core/include/opencv2/core/eigen.hpp.

  • cv::Mat can now be print with "<<" operator. See opencv/samples/cpp/cout_mat.cpp.

  • cv::exp and cv::log are now much faster thanks to SSE2 optimization.
• imgproc:
  • color conversion functions have been rewritten;

    • RGB->Lab & RGB->Luv performance has been noticeably improved. Now the functions assume sRGB input color space (e.g. gamma=2.2). If you want the original linear RGB->L** conversion (i.e. with gamma=1), use CV_LBGR2LAB etc.

    • VNG algorithm for Bayer->RGB conversion has been added. It's much slower than the simple interpolation algorithm, but returns significantly more detailed images

    • The new flavors of RGB->HSV/HLS conversion functions have been added for 8-bit images. They use the whole 0..255 range for the H channel instead of 0..179. The conversion codes are CV_RGB2HSV_FULL etc.

  • special variant of initUndistortRectifyMap for wide-angle cameras has been added: initWideAngleProjMap()
• features2d:

  • the unified framework for keypoint extraction, computing the descriptors and matching them has been introduced. The previously available and some new detectors and descriptors, like SURF, Fast, StarDetector etc. have been wrapped to be used through the framework. The key advantage of the new framework (besides the uniform API for different detectors and descriptors) is that it also provides high-level tools for image matching and textured object detection. Please, see documentation http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html

    • and the C++ samples:
      • descriptor_extractor_matcher.cpp - finding object in a scene using keypoints and their descriptors.
      • generic_descriptor_matcher.cpp - variation of the above sample where the descriptors do not have to be computed explicitly.
      • bagofwords_classification.cpp - example of extending the framework and using it to process data from the VOC databases:

        • http://pascallin.ecs.soton.ac.uk/challenges/VOC/

  • the newest super-fast keypoint descriptor BRIEF by Michael Calonder has been integrated by Ethan Rublee. See the sample opencv/samples/cpp/video_homography.cpp
  • SURF keypoint detector has been parallelized using TBB (the patch is by imahon and yvo2m)
• objdetect:
  • LatentSVM object detector, implementing P. Felzenszwalb algorithm, has been contributed by Nizhniy Novgorod State University (NNSU) team. See
    • opencv/samples/c/latentsvmdetect.cpp
• calib3d:
  • The new rational distortion model:

    • x' = x*(1 + k₁*r² + k₂*r⁴ + k₃*r⁶)/(1 + k₄*r² + k₅*r⁴ + k₆*r⁶) + <tangential_distortion for x>,

      y' = y*(1 + k₁*r² + k₂*r⁴ + k₃*r⁶)/(1 + k₄*r² + k₅*r⁴ + k₆*r⁶) + <tangential_distortion for y>

    • has been introduced. It is useful for calibration of cameras with wide-angle lenses. Because of the increased number of parameters to optimize you need to supply more data to robustly estimate all of them. Or, simply initialize the distortion vectors with zeros and pass

      CV_CALIB_RATIONAL_MODEL to enable the new model + CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5 or other such combinations to selectively enable or disable certain coefficients.

  • rectification of trinocular camera setup, where all 3 heads are on the same line, is added. see samples/cpp/3calibration.cpp
• ml:
  • Gradient boosting trees model has been contributed by NNSU team.
• highgui:

  • Experimental Qt backend for OpenCV has been added as a result of GSoC 2010 project, completed by Yannick Verdie. The backend has a few extra features, not present in the other backends, like text rendering using TTF fonts, separate "control panel" with sliders, push-buttons, checkboxes and radio buttons, interactive zooming, panning of the images displayed in highgui windows, "save as" etc. Please, check the youtube videos where Yannick demonstrates the new features: http://www.youtube.com/user/MrFrenchCookie#p/u

  • The new API is described here: http://opencv.willowgarage.com/documentation/cpp/highgui_qt_new_functions.html To make use of the new API, you need to have Qt SDK (or libqt4 with development packages) installed on your machine, and build OpenCV with Qt support (pass -DWITH_QT=ON to CMake; watch the output, make sure Qt is used as GUI backend)

  • 16-bit and LZW-compressed TIFFs are now supported.
  • You can now set the mode for IEEE1394 cameras on Linux.
• contrib:
  • Chamfer matching algorithm has been contributed by Marius Muja, Antonella Cascitelli, Marco Di Stefano and Stefano Fabri. See samples/cpp/chamfer.cpp
• gpu:
  • This is completely new part of OpenCV, created with the support by NVidia. Note that the package is at alpha, probably early beta state, so use it with care and check OpenCV SVN for updates.

    In order to use it, you need to have the latest NVidia CUDA SDK installed, and build OpenCV with CUDA support (-DWITH_CUDA=ON CMake flag). All the functionality is put to cv::gpu namespace. The full list of functions and classes can be found at opencv/modules/gpu/include/opencv2/gpu/gpu.hpp, and here are some major components of the API:

    • image arithmetics, filtering operations, morphology, geometrical transformations, histograms
    • 3 stereo correspondence algorithms: Block Matching, Belief Propagation and Constant-Space Belief Propagation.
    • HOG-based object detector. It runs more than order of magnitude faster than the CPU version!
      • See opencv/samples/gpu
• python bindings:
  • A lot more of OpenCV 2.x functionality is now covered by Python bindings.
    • These new wrappers require numpy to be installed

      • (see http://opencv.willowgarage.com/wiki/InstallGuide for details).

      Likewise the C++ API, in the new Python bindings you do not need to allocate output arrays. They will be automatically created by the functions. Here is a micro example:

      •       import cv
        
              a=cv.imread("lena.jpg",0)
              b=cv.canny(a, 50, 100, apertureSize=3)
              cv.imshow("test",b)
              cv.waitKey(0)

        In the sample a and b are normal numpy arrays, so the whole power of numpy and scipy can now be combined with OpenCV functionality.

Documentation, Samples

• Links to wiki pages (mostly empty) have been added to each function description, see http://opencv.willowgarage.com

• All the samples have been documented with default output (0 or incomplete number of parameters) set to print out "howto" run instructions [Gary]; most samples have been converted to C++ to use the new OpenCV API.

Bug Fixes

• Over 300 issues have been resolved. Most of the issues (closed and still open) are listed at https://code.ros.org/trac/opencv/report/6.

• The old bug tracker at https://sourceforge.net/projects/opencvlibrary/ is now closed for updates. As soon as all the still relevant bug reports will be moved to code.ros.org, the old bug tracker will be completely deleted. Please, use the new tracker from now on.

Known Problems/Limitations

• Installation package for Windows is still 32-bit only and does not include TBB support. You can build parallel or 64-bit version of OpenCV from the source code.

• The list of the other open bugs can be found at http://code.ros.org/trac/opencv/report/1.

2.1

(April, 2010)

General Modifications

• - SVN repository has been migrated from SourceForge to https://code.ros.org/svn/opencv.

  • The bug tracker has been moved to https://code.ros.org/trac/opencv/. And we also have OpenCV twitter! http://twitter.com/opencvlibrary

  - The whole OpenCV is now using exceptions instead of the old libc-style mechanism.
  • That is, instead of checking error code with cvGetErrStatus() (which currently always returns 0) you can now just call OpenCV functions inside C++ try-catch statements, cv::Exception is now derived from std::exception.
  - OpenCV does not support autotools-based build scripts,
  • CMake (www.cmake.org) is the only way to build OpenCV on any OS.

    See http://opencv.willowgarage.com/wiki/InstallGuide.

  - All the parallel loops in OpenCV have been converted from OpenMP

  • to Intel TBB (http://www.threadingbuildingblocks.org/). Thus parallel version of OpenCV can now be built using MSVC 2008 Express Edition or using earlier than 4.2 versions of GCC.

  - SWIG-based Python wrappers are still included,
  • but they are not built by default and it's generally preferable to use the new wrappers. The python samples have been rewritten by James Bowman to use the new-style Python wrappers, which have been also created by James.
  - OpenCV can now be built and run in 64-bit mode on MacOSX 10.6 and Windows (see HighGUI and known problems below).
  • On Windows both MSVC 2008 and mingw64 are known to work.
  - In theory OpenCV is now able to determine the host CPU on-fly and make use of SSE/SSE2/... instructions,
  • if they are available. That is, it should be more safe to use WITH_SSE* flags in CMake. However, if you want maximum portability, it's recommended to turn on just WITH_SSE and WITH_SSE2 and leave other SSE* turned off, as we found that using WITH_SSE3, WITH_SSSE3 and WITH_SSE4_1 can yield the code incompatible with Intel's pre-Penryn or AMD chips.
  - Experimental "static" OpenCV configuration in CMake was contributed by Jose Luis Blanco.
  • Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically.

New Functionality, Features

• - cxcore, cv, cvaux:

  • Grabcut (http://en.wikipedia.org/wiki/GrabCut) image segmentation algorithm has been implemented.

    • See opencv/samples/c/grabcut.cpp
  • new improved version of one-way descriptor is added. See opencv/samples/c/one_way_sample.cpp
  • modified version of H. Hirschmuller semi-global stereo matching algorithm that we call SGBM
    • (semi-global block matching) has been created. It is much faster than Kolmogorov's graph cuts-based algorithm and yet it's usually better than the block matching StereoBM algorithm. See opencv/samples/c/stereo_matching.cpp.
  • existing StereoBM stereo correspondence algorithm by K. Konolige was noticeably improved:
    • added the optional left-right consistency check and speckle filtering, improved performance (by ~20%).
  • User can now control the image areas visible after the stereo rectification
    • (see the extended stereoRectify/cvStereoRectify), and also limit the region where the disparity is computed (see CvStereoBMState::roi1, roi2; getValidDisparityROI).
  • Mixture-of-Gaussian based background subtraction algorithm has been rewritten for better performance

    • and better accuracy. Alternative C++ interface BackgroundSubtractor has been provided, along with the possibility to use the trained background model to segment the foreground without updating the model. See opencv/samples/c/bgfg_segm.cpp.

  - highgui:
  • MacOSX: OpenCV now includes Cocoa and QTKit backends, in addition to Carbon and Quicktime.
    • Therefore you can build OpenCV as 64-bit library. Thanks to Andre Cohen and Nicolas Butko, which components Note however that the backend are now in the alpha state, they can crash or leak memory, so for anything more serious than quick experiments you may prefer to use Carbon and Quicktime. To do that, pass USE_CARBON=ON and USE_QUICKTIME=ON to CMake and build OpenCV in 32-bit mode (i.e. select i386 architecture in Xcode).
  • Windows. OpenCV can now be built in 64-bit mode with MSVC 2008 and also mingw64.
  • Fullscreen has been added (thanks to Yannick Verdie).
    • Call cvSetWindowProperty(window_name, CV_WINDOW_FULLSCREEN, 1) to make the particular window to fill the whole screen. This feature is not supported in the Cocoa bindings yet.
  • gstreamer backend has been improved a lot (thanks to Stefano Fabri)

New Tests

• - A few dozens of new tests have been written and many existing tests have been extended
  • to verify OpenCV correctness thoroughly. As a result, we brought the test coverage from rather mediocre numbers to pretty impressive ones (especially for cxcore and cv)!

    Module	OpenCV 2.0 coverage, % (functions/conditions)	OpenCV 2.1 coverage, % (functions/conditions)
    cxcore	65/54	91/73
    cv	52/46	80/68
    ml	66/47	73/52
    highgui	17/3	54/27
    cvaux	0/0	5/12

  - Many new regression tests have been written in Python that check both OpenCV and the new-style bindings.

  - The test data moved to the separate repository: https://code.ros.org/svn/opencv/trunk/opencv_extra/testdata.

  • And it is not included into the package, thus some tests from the cvtest and mltest will report about the missing data. You can download the directory to your hard drive and run cvtest like:

        ./cvtest -d <path_to_opencv_extra>/testdata/cv
        ./mltest -d <path_to_opencv_extra>/testdata/ml

  - The test engine has been improved:
  • added flags -tn, -seed, -r the detailed information about failed tests is displayed right in the console.

Bug Fixes

• - about 200 bugs have been fixed. For the list of closed and still open bugs, please look at

  • https://code.ros.org/trac/opencv/report and http://sourceforge.net/tracker/?group_id=22870&atid=376677.

Known Problems/Limitations

• - there are some sporadic test failures on different platforms.
  • Most probably they are caused by some very special test cases (that are usually generated randomly on each test run), and the test cases are not properly handled by the functions or by the tests. Some of the tests have been reproduced and reported here:

    https://code.ros.org/trac/opencv/ticket/29 https://code.ros.org/trac/opencv/ticket/113 https://code.ros.org/trac/opencv/ticket/114

  - the new Python bindings do not include interface for the new C++ functionality and MLL.
  • this is going to be addressed in some special intermediate OpenCV release
  - documentation is also incomplete at the moment and there are occasional formatting,
  • grammar and semantical errors. We continue to improve it on a regular basis. Please, check the up-to-date online documentation at:

    http://opencv.willowgarage.com/documentation/c/index.html (C) http://opencv.willowgarage.com/documentation/cpp/index.html (C++) http://opencv.willowgarage.com/documentation/python/index.html (Python)

  - please also check the list of open bugs at

  • https://code.ros.org/trac/opencv/report and http://sourceforge.net/tracker/?group_id=22870&atid=376677.

2.0

(September, 2009)

New functionality, features:

• - General:

  • Installation package on Windows has been fixed, MinGW is used for precompiled binaries (see the release notes on the SourceForge site)

  • autotools-based build has been repaired
  • New Python interface officially in.
  - MLL:

  • The new-style class aliases (e.g. cv::SVM ~ CvSVM) and the train/predict methods, taking cv::Mat in addition to CvMat, have been added. So now MLL can be used more seamlesly with the rest of the restyled OpenCV.

Bug fixes:

Thanks to everybody who submitted bug reports and/or patches!

• A _lot_ of bugs present in 2.0 beta have been fixed, see the OpenCV bug tracker

  • http://sourceforge.net/tracker/?group_id=22870&atid=376677

2.0 beta

(September, 2009)

New functionality, features:

• General:

  • The brand-new C++ interface for most of OpenCV functionality (cxcore, cv, highgui) has been introduced. Generally it means that you will need to do less coding to achieve the same results; it brings automatic memory management and many other advantages.
    • See the C++ Reference section in opencv/doc/opencv.pdf and opencv/include/opencv/*.hpp.
      • The previous interface is retained and still supported.
  • The source directory structure has been reorganized; now all the external headers are placed in the single directory on all platforms.
  • The primary build system is CMake,

    • http://www.cmake.org (2.6.x is the preferable version).

      • In Windows package the project files for Visual Studio, makefiles for MSVC, Borland C++ or MinGW are not supplied anymore; please, generate them using CMake.
      • In MacOSX the users can generate project files for Xcode.
      • In Linux and any other platform the users can generate project files for cross-platform IDEs, such as Eclipse or Code Blocks, or makefiles for building OpenCV from a command line.

  • OpenCV repository has been converted to Subversion, hosted at SourceForge:

    • http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary

    • where the very latest snapshot is at

      • http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/trunk,

    • and the more or less stable version can be found at

      • http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/tags/latest_tested_snapshot

• CXCORE, CV, CVAUX:

  • CXCORE now uses Lapack (CLapack 3.1.1.1 in OpenCV 2.0) in its various linear algebra functions (such as solve, invert, SVD, determinant, eigen etc.) and the corresponding old-style functions (cvSolve, cvInvert etc.
  • Lots of new feature and object detectors and descriptors have been added (there is no documentation on them yet), see cv.hpp and cvaux.hpp:

    • FAST - the fast corner detector, submitted by Edward Rosten

    • MSER - maximally stable extremal regions, submitted by Liu Liu

    • LDetector - fast circle-based feature detector

      • by V. Lepetit (a.k.a. YAPE)

    • Fern-based point classifier and the planar object detector -

      • based on the works by M. Ozuysal and V. Lepetit

    • One-way descriptor - a powerful PCA-based feature descriptor,

      • S. Hinterstoisser, O. Kutter, N. Navab, P. Fua, and V. Lepetit, "Real-Time Learning of Accurate Patch Rectification". Contributed by Victor Eruhimov

    • Spin Images 3D feature descriptor

      • based on the A. Johnson PhD thesis; implemented by Anatoly Baksheev

    • Self-similarity features - contributed by Rainer Leinhar

    • HOG people and object detector - the reimplementation of Navneet Dalal framework

      • (http://pascal.inrialpes.fr/soft/olt/). Currently, only the detection part is ported, but it is fully compatible with the original training code.

      • See cvaux.hpp and opencv/samples/c/peopledetect.cpp.
    • LBP (Local Binary Pattern) features

    • Extended variant of the Haar feature-based object detector - implemented by Maria Dimashova. It now supports Haar features and LBPs, other features can be added in the same way.

    • Adaptive skin detector and the fuzzy meanshift tracker - contributed by Farhad Dadgostar, see cvaux.hpp and opencv/samples/c/adaptiveskindetector.cpp

  • The new traincascade application complementing the new-style HAAR+LBP object detector has been added. See opencv/apps/traincascade.

  • The powerful library for approximate nearest neighbor search FLANN by Marius Muja is now shipped with OpenCV, and the OpenCV-style interface to the library is included into cxcore. See cxcore.hpp and opencv/samples/c/find_obj.cpp

  • The bundle adjustment engine has been contributed by PhaseSpace; see cvaux.hp

  • Added dense optical flow estimation function based on the paper

    • "Two-Frame Motion Estimation Based on Polynomial Expansion" by G. Farnerback.

    • See cv::calcOpticalFlowFarneback and the C++ documentation
  • Image warping operations (resize, remap, warpAffine, warpPerspective) now all support bicubic and Lanczos interpolation.
  • Most of the new linear and non-linear filtering operations (filter2D, sepFilter2D, erode, dilate ...) support arbitrary border modes and can use the valid image pixels outside of the ROI (i.e. the ROIs are not "isolated" anymore), see the C++ documentation.
  • The data can now be saved to and loaded from GZIP-compressed XML/YML files, e.g.: cvSave("a.xml.gz", my_huge_matrix);

• MLL:

  • Added the Extremely Random Trees that train super-fast, comparing to Boosting or Random Trees (by Maria Dimashova).

  • The decision tree engine and based on it classes (Decision Tree itself, Boost, Random Trees) have been reworked and now:
    • they consume much less memory (up to 200% savings)
    • the training can be run in multiple threads (when OpenCV is built with OpenMP support)
    • the boosting classification on numerical variables is especially fast because of the specialized low-overhead branch.
  • mltest has been added. While far from being complete, it contains correctness tests for some of the MLL classes.

• HighGUI:

  • [Linux] The support for stereo cameras (currently Videre only) has been added.
  • There is now uniform interface for capturing video from two-, three- ... n-head cameras.
  • Images can now be compressed to or decompressed from buffers in the memory, see the C++ HighGUI reference manual

• Documentation:

  • The reference manual has been converted from HTML to LaTeX (by James Bowman and Caroline Pantofaru), so there is now:

    • opencv.pdf for reading offline

    • and the online up-to-date documentation (as the result of LaTeX->Sphinx->HTML conversion) available at

      • http://opencv.willowgarage.com/documentation/index.html

• Samples, misc.:

  • Better eye detector has been contributed by Shiqi Yu, see opencv/data/haarcascades/*[lefteye|righteye]*.xml

  • sample LBP (Local Binary Pattern) cascade for the frontal face detection has been created by Maria Dimashova, see opencv/data/lbpcascades/lbpcascade_frontalface.xml

  • Several high-quality body parts and facial feature detectors have been

    • contributed by Modesto Castrillon-Santana,

    • see opencv/data/haarcascades/haarcascade_mcs*.xml

Optimization:

• Many of the basic functions and the image processing operations(like arithmetic operations, geometric image transformations, filtering etc.) have got SSE2 optimization, so they are several times faster.
• The model of IPP support has been changed. Now IPP is supposed to be detected by CMake at the configuration stage and linked against OpenCV. (In the beta it is not implemented yet though).
• PNG encoder performance improved by factor of 4 by tuning the parameters

Bug fixes:

Many thanks to everybody who submitted bug reports and/or provided the patches!

• see http://sourceforge.net/tracker/?group_id=22870&atid=376677 of the list of the closed and still opened bugs.

Known issues:

• configure+autotools based build is currently broken. Please, use CMake.
• OpenCV bug tracker at SF still lists about 150 open bugs. Some of them may be actually fixed already, and most of the remaining bugs are going to be fixed by OpenCV 2.0 gold.
• IPP is not supported. As the new OpenCV includes a lot of SSE2 code, it may be not such a serious problem, though. The support (at least for most important functions that do not have SSE2 optimization) will be returned in 2.0 gold.
• The documentation has been updated and improved a lot, but it still needs quite a bit of work:
  • some of the new functionality in cvaux is not described yet.
  • the bibliography part is broken
  • there are quite a few known bugs and typos there
  • many of the hyperlinks are not working.
• The existing tests partly cover the new functionality (via the old backward-compatibility OpenCV 1.x API), but the coverage is not sufficient of course.
• The new-style Python interface is not included yet

• Many of the problems will be addressed in 2.0 gold. If you have found some specific problem, please, put the record to the bug tracker:

  • http://sourceforge.net/tracker/?group_id=22870

  • Better if the bug reports will include a small code sample in C++/python + all the necessary data files needed to reproduce the problem.

1.1pre1

(October, 2008)

New functionality/features:

• General:

  • Octave bindings have been added. See interfaces/swig/octave (for now, Linux only)
  • [Windows] OpenCV is now built with VS2005 with SSE2 and OpenMP support included (if you want to rebuild OpenCV using Express or Standard Edition of VS, use _make\opencv.vs2005.no_openmp.sln).
  • [Windows] Python bindings have been updated to use Python 2.6
  • [Windows] cvcam has been removed (as videoInput is now supported by highgui)

• CXCORE, CV, CVAUX:

  • Speeded-up Robust Features (SURF), contributed by Liu Liu. see samples/c/find_obj.cpp and the documentation opencvref_cv.htm
  • Many improvements in camera calibration:
    • Added stereo camera calibration: cvStereoCalibrate, cvStereoRectify etc.
    • Single camera calibration now uses Levenberg-Marquardt method and supports extra flags to switch on/off optimization of individual camera parameters
    • The optional 3rd radial distortion parameter (k3*r^6) is now supported in every calibration-related function
  • 2 stereo correspondence algorithms:

    • very fast block matching method by Kurt Konolige (processes the Tsukuba stereo pair in <10ms on Core2Duo laptop)

    • slow but more accurate graph-cut based algorithm by Kolmogorov and Zabin
  • Better homography estimation algorithms (RANSAC and LMEDs)
  • new C++ template image classes contributed by Daniel Filip (Google inc.). see opencv/cxcore/include/cvwimage.h
  • Fast approximate nearest neighbor search (by Xavier Delacour)
  • Codebook method for background/foreground segmentation (by Gary Bradski)
  • Sort function (contributed by Shiqi Yu)
  • [OpenCV+IPP] Face Detection (cvHaarDetectObjects) now runs much faster (up to 2x faster) when using IPP 5.3 or higher.
  • Much faster (~4x faster) fixed-point variant of cvRemap has been added

• MLL:

  • Python bindings for MLL have been added. There are no samples yet.

• HighGUI:

  • [Windows, 32bit] Added support for videoInput library. Hence, cvcam is [almost] not needed anymore
  • [Windows, 32bit] FFMPEG can now be used for video decoding/encoding via ffopencv*.dll
  • [Linux] Added unicap support
  • Improved internal video capturing and video encoding APIs

• Documentation:

  • OpenCV book has been published (sold separately see docs/index.htm)

• New samples (opencv/samples):

  • Many Octave samples
  • find_obj.cpp (SURF), bgfg_codebook.cpp (Codebook BG/FG segmentation),
    • stereo_calib.cpp (Stereo calibration and stereo correspondence)

Bug fixes:

Many thanks to everybody who submitted bug reports and/or provided the patches!

• added dma_unlisten to icvCloseCAM_DC1394 (thanks to Victor Benso)
• LMEDs algorithm for cvFindFundamentalMat estimation has been fixed
• Broken debug build of highgui in VS2005/2008 (SF #2056185, SF #1709435)
• cvFindChessboardCorners memory leak and incorrect size checks (SF #1972896, SF #1910323)
• disabling GTK causes v4l runtime error (SF #2088102)
• cvsetmousecallback bug (SF #2053529)
• libhighgui needed deprecated "img_convert" replacement (SF #2011753)
• Segfault in createsamples caused by uninitialized variable (SF #1977989)
• Data Alignment Issue in bgfg_gaussmix (SF #1961755)
• libpng need to be updated (SF #1952793)
• cvCreateVideoWriter_Win32 - identifier not found (SF #1944254)
• Bug in cvmorph.cpp (SF #1908844)
• dilate (cvDilate) works bogus with default kernel (SF #1887130)
• CvEM non-default constructor declared but not defined (SF #1830346)
• cvFloodFill (in ver 1.0) Hangs (SF #1790565)

• double delete in CvImage (SF #1733437)

• cvFilter2D anchor default value is not working properly (SF #1713779)
• cvCvtColor - Bug? in converting HSV2RGB (SF #1676344)
• Invalid selection of the MKL-dll version in cvUseOptimized() (SF #1633017)
• ...

Known issues:

• Borland compiler is not supported (but might work) in this update.
• 64-bit Windows is not supported (but might work) in this update.
• SF bug tracker still contains over 50 records of open bugs.
  • Many of them will be addressed in the next update.

1.0

(October, 2006)

New functionality/features:

• General:

  • Windows installation package now includes precompiled Python module
  • Borland C++ (v5.6+) makefiles re-added (see _make\make_all_bc.mak)

• CV:

  • Inpainting was added, see samples/c/inpaint.cpp (thanks to Alexander Kibkalo and Alexey Kalinichenko)

• MLL:

  • Boosted tree classifiers added, see MLL reference manual

• HighGUI:

  • Jpeg2000 and EXR support in highgui using JasPer and OpenEXR (thanks to Nils Hasler) OpenEXR is not built-in to highgui on Windows by default. See otherlibs/_graphics/readme.txt.

  • >8-bit image input/output for PNG, Jpeg2000 and OpenEXR (thanks to Nils Hasler)

  • Updated CMUcamera wrapper.

  • Several V4L2 improvements and fixes

• New samples (opencv/samples):

  • Camera calibration sample: calibrate.cpp
  • Inpainting sample: inpaint.cpp
  • Letter recognition using the existing database with random trees/boosted trees/neural nets: leter_recog.cpp
  • A few new Python samples.

• Tests:

  • Most old cv tests have been rewritten/converted to use cxts instead of trs. TRS is not used by the tests anymore.

Bug fixes:

Many thanks to everybody who submitted bug reports and/or provided the patches!

• Incorrect normalization in cvFindFundamentalMat (SF #1550855)
• Occasional cvGetQuadrangleSubPix crashes (SF #1549168)
• Occasional cvCalcOpticalFlowPyrLK crashes
• Internal GCC 3.x error in cvFloor/cvCeil (SF #1546657)
• Several Python-related bugs (SF #1570109, SF #1572800, SF #1543593)
• Bugs in contour processing/rendering (SF #1550889,
• x86-64 related bugs (SF #1526133, SF #1527997)
• OpenCV dispatcher tried to load old versions of IPP (pre 4.x) that caused many failures (see SF #1555093, for example)
• Inaccurate results in some cases in cvFitEllipse, cvFitLine, cvHoughCircles.
• Severe bug in Bayesian classifier, broken regression tree in MLL
• Overflow in blurring filter
• cvSaveImage() modified saved images leading to potential problems in threaded apps.
• Numeric values in XML/YAML were emitted/parsed incorrectly on some non-US locales in Linux
• VS2005 Express/Standard Editions could not build OpenCV (due to missing OpenMP support)
• ...

Known issues:

• Certain tests may fail on IA64 (Itanium), e.g.
  • gaussian filter, fundamental matrix estimation, chessboard detector.

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