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OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]). The library is cross-platform and licensed as free and open-source software under Apache License ...
Computer Vision Annotation Tool (CVAT) is an open source, web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel, CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision annotation tasks.
Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos.From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
A recent algorithm for solving the problem as well as a solution classification for it is given in the 2003 IEEE Transactions on Pattern Analysis and Machine Intelligence paper by Gao, et al. [6] An open source implementation of Gao's P3P solver can be found in OpenCV's calib3d module in the solvePnP function. [7]
Cinelerra 2.1 being used to edit footage in a video project. Cinelerra is a video editing and track-based digital compositing program (an NLE, Non-Linear Editor) designed for Linux. It is free software distributed under the open source GNU General Public License.
English: The OpenCV logo is composed of the 3 capital letters O, C, V arranged in a triangle. The logo combines several motifs in the spirit of Open Source and Computer Vision . SVG-version.
Demosaicing (or de-mosaicing, demosaicking), also known as color reconstruction, is a digital image processing algorithm used to reconstruct a full color image from the incomplete color samples output from an image sensor overlaid with a color filter array (CFA) such as a Bayer filter.
The basic eight-point algorithm is here described for the case of estimating the essential matrix .It consists of three steps. First, it formulates a homogeneous linear equation, where the solution is directly related to , and then solves the equation, taking into account that it may not have an exact solution.