OpenCV and Intel have a long history of fruitful collaboration. OpenCV project has been started at Intel back in 1998, with the first public release in 2000. Even now, 20 years later, Intel Corporation still funds the core OpenCV development team and maintains the build farm.
OpenCV is well-optimized for Intel platforms, in particular:
- A subset of Intel IPP (https://software.intel.com/en-us/ipp) is included by default to OpenCV builds on Intel platforms. This subset of IPP, called IPPICV, is free for all OpenCV users. IPP accelerates a number of kernels in OpenCV, mostly the image processing.
- Intel MKL (https://software.intel.com/en-us/mkl) can optionally be used as well, to get some matrix operations accelerated.
- Intel TBB (https://software.intel.com/en-us/tbb) is another optional component that OpenCV can be linked with to get a better scalability on many-core Intel CPUs.
- Intel Media SDK (https://software.intel.com/en-us/media-sdk) is yet another library that can optionally be used within OpenCV to enable hardware-accelerated video decoding/encoding. Another option to get the same effect is to use gstreamer backend in OpenCV VideoIO module, as long as the proper gstreamer plugins are installed.
The last but definitely not the least library that OpenCV can greatly benefit from on Intel platforms is
OpenVINO is open-source collection of tools and models to enable highly-efficient AI solutions across a variety of Intel platforms. The Intel distribution of OpenVINO (https://software.intel.com/en-us/openvino-toolkit) includes a custom optimized build of OpenCV, as well as high-performance deep learning inference engine and a bunch of other tools. The Intel inference engine can be used as a standalone library or as an accelerator for OpenCV DNN module:
The users of OpenVINO can also enjoy a collection of pre-trained high-quality free deep learning models: https://github.com/opencv/open_model_zoo covering a broad range of computer vision applications.