Search results
Results From The WOW.Com Content Network
cvsba Archived 2013-10-24 at the Wayback Machine: An OpenCV wrapper for sba library . GPL. ssba: Simple Sparse Bundle Adjustment package based on the Levenberg–Marquardt Algorithm (C++). LGPL. OpenCV: Computer Vision library in the Images stitching module. BSD license. mcba: Multi-Core Bundle Adjustment (CPU/GPU). GPL3.
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]).
It is written in C++ and released under the BSD license. These algorithms have been used, for example, for perception in robotics to filter outliers from noisy data, stitch 3D point clouds together , segment relevant parts of a scene, extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance ...
A C++ implementation is available on GitHub, which has also been ported to OpenCV and included in the Camera Calibration and 3D Reconstruction module (SolvePnP function). [ 12 ] Using RANSAC
OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.
A simple elastic snake is defined by a set of n points for =, …,, the internal elastic energy term , and the external edge-based energy term .The purpose of the internal energy term is to control the deformations made to the snake, and the purpose of the external energy term is to control the fitting of the contour onto the image.
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.
OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.