Open Source C++ Realtime Processing Software for Linux

The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html

reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.

The Integrating Vision Toolkit (IVT) is a powerful and fast C++ computer vision library with an easy-to-use object-oriented architecture. It offers its own multi-platform GUI toolkit. OpenCV is integrated optionally. Website: http://ivt.sourceforge.net

C++ Computer vision library

Video processing and computer vision library for GNU/Linux offering interfaces to do image- and video-I/O with ImageMagick/Magick++, Xine, firewire digital camera (DC1394), and video for linux (V4L2). Note that this version of HornetsEye is deprecated. HornetsEye now is released as multiple packages on RubyGems.org. The source code is available on Github.com (see https://wedesoft.github.io/hornetseye-doc/ for more information).

Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters, implemented in OpenCL. The framework was mainly designed as a toolkit for the rapid development of interactive art projects that explore dynamics of complex environments. The Scene GUI runs and compiles under Windows, Linux, and MacOS X, and is available in both 32 bit and 64 bit versions.

The webcam computer vision (WCCV) project focuses on computer vision algorithms and systems that follow the web cam paradigm: cheap, robust and efficient. The project comprises designs, patterns, code, tutorials and examples.

The Mimas Toolkit is a C++ real-time computer vision library. Algorithms include edge/corner-detection, object recognition/tracking, LSI-filters, segmentation, array-operators, convolution etc. OO wrappers for LAPACK, libxine, V4L, FFTW are provided.