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The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.
opencv.github.io /cvat /about / Computer Vision Annotation Tool (CVAT) is a free, open source , web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision ...
OpenVX is an open, royalty-free standard for cross-platform acceleration of computer vision applications. It is designed by the Khronos Group to facilitate portable, optimized and power-efficient processing of methods for vision algorithms.
VXL is a larger-scale software engineering project with roots dating back to traditional computer vision environments from the 1990s, having libraries at multiple levels of complexities, many of them listing OpenCV as one of many dependencies. A similar approach at an even larger scale is taken by Kitware's KWIVER. [2]
Gary Bradski is an American scientist, engineer, entrepreneur, and author. He co-founded Industrial Perception, a company that developed perception applications for industrial robotic application (since acquired by Google in 2012 [2]) and has worked on the OpenCV Computer Vision library, as well as published a book on that library.
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Originally published in 2006, Kaehler's book Learning OpenCV (O'Reilly) serves as an introduction to the library and its use. The book continues to be heavily used by both professionals and students. An updated version of the book, which covers OpenCV 3, was published by O'Reilly Media in 2016. [5]
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