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In computer vision, the Kanade–Lucas–Tomasi (KLT) feature tracker is an approach to feature extraction. It is proposed mainly for the purpose of dealing with the problem that traditional image registration techniques are generally costly. KLT makes use of spatial intensity information to direct the search for the position that yields the ...
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 ...
In computer vision, the Lucas–Kanade method is a widely used differential method for optical flow estimation developed by Bruce D. Lucas and Takeo Kanade.It assumes that the flow is essentially constant in a local neighbourhood of the pixel under consideration, and solves the basic optical flow equations for all the pixels in that neighbourhood, by the least squares criterion.
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]
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]
Roundup was designed by Ka-Ping Yee for the Software Carpentry project and was developed from 2001 to 2016 under the direction of Richard Jones. Since then, it has been developed by the Roundup community. It was the issue tracker for the Python programming language for 17 years before migrating to GitHub. [4]
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.
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.