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Perspective-n-Point [1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image.
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.
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.
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.
The process of Canny edge detection algorithm can be broken down to five different steps: Apply Gaussian filter to smooth the image in order to remove the noise; Find the intensity gradients of the image
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A curve (top) is filled according to two rules: the even-odd rule (left), and the non-zero winding rule (right). In each case an arrow shows a ray from a point P heading out of the curve.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]