OpenCV, an open-source computer visionlibrary, has more than 14 million downloads in total, and has been used in a number of different computer vision applications, including platforms ranging from the cloud to mobile devices.
Recently, version 3.1 was released, which introduces support for deep neural networks, as well as new and improved algorithms for important functions such as calibration, optical flow, image filtering, segmentation and feature detection.
Gary Bradski, President and CEO of the OpenCV Foundation, recently presented on the topic at the May 2016 Embedded Vision Summit. His presentation "The OpenCV Open Source Computer Vision Library: What’s New and What’s Coming?" provides insight OpenCV 3.1, and how developers can utilize it to its maximum advantage for vision research, prototyping, and product development. He also takes a look at where OpenCV is headed next.
Check out Bradski’s entire presentation in this photo slideshow:
