OpenCV
was started at Intel in 1999 by Gary Bradsky and the first release
came out in 2000. Vadim Pisarevsky joined Gary Bradsky to manage
Intel’s Russian software OpenCV team. In 2005, OpenCV was used on
Stanley, the vehicle who won 2005 DARPA Grand Challenge. Later its
active development continued under the support of Willow Garage, with
Gary Bradsky and Vadim Pisarevsky leading the project. Right
now, OpenCV supports a lot of algorithms related to Computer Vision
and Machine Learning and it is expanding day-by-day.
Currently
OpenCV supports a wide variety of programming languages like C++,
Python, Java etc and is available on different platforms including
Windows, Linux, OS X, Android, iOS etc. Also, interfaces based on
CUDA and OpenCL are also under active development for high-speed GPU
operations.
OpenCV
is a cross-platform library using which we can develop real-time
computer vision applications. It mainly focuses on image processing,
video capture and analysis including features like face detection and
object detection. In this tutorial, we explain how you can use OpenCV
in your applications.
