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文章标签 ‘background subtraction’

vibe

2011年12月25日 18 条评论

– a powerful technique for background detection and subtraction in video sequences

Executive summary

Description

ViBe is a powerful pixel-based technique that detects the background in video sequences. Many experiments have shown that it performs better than the state-of-the-art techniques known in the scientific literature. In addition the computational load is lower than simple background techniques implemented in commercial products. ViBe is the perfect solution for both software and hardware implementations.

Code and program for Windows and Linux
  • A program for Windows and Linux. Download an archive zip archive [10 MB - updated on May 19, 2011] to use ViBe on Windows (or under Wine in Linux). Details on this page.
    The program allows you to: (1) save the result for your own images, (2) change the few parameters of ViBe to experiment with, and (3) reproduce our results.
  • Linux: link a C/C++ object file to your own code. We provide the object (compiled) code of ViBe for non-commercial applications. Under Linux, download the 32 bits zip or compressed tar file, or the 64 bits zip or compressed tar file. Details on this page.

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OpenCV 2.1 发布

2010年4月10日 1 条评论

Open Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library IconOpen Computer Vision Library Icon

来源如下：

http://sourceforge.net/mailarchive/forum.php?thread_name=s2y619b2d671004051902n71c46746m5dc42581ca1d4a79@mail.gmail.com&forum_name=opencvlibrary-devel

贴个changelog里的新添加的features：

>>> New functionality, features:
- cxcore, cv, cvaux:
* (http://en.wikipedia.org/wiki/) image segmentation algorithm has been implemented.
See /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 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.
还有几个链接：

The packages are available at SourceForge (
https://sourceforge.net/projects/opencvlibrary/files/).
The detailed ChangeLog is here:
https://code.ros.org/svn/opencv/trunk/opencv/doc/ChangeLog.htm.
The installation guide is here:
http://opencv.willowgarage.com/wiki/InstallGuide

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