SONIC is an object-oriented optical navigation (OPNAV) toolkit written in MATLAB.
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Updated
Jun 28, 2024 - MATLAB
SONIC is an object-oriented optical navigation (OPNAV) toolkit written in MATLAB.
This repository contains the code for extrensic and intrinsic camera calibration for poses obtained via OptiTrack using the OpenCV library.
structure from motion (SfM) is the process of estimating the 3D structure of a scene from a set of 2D images. here I estimate the poses of a calibrated camera from two images, reconstruct the 3D structure of the scene up to an unknown scale factor, and then recover the actual scale factor by detecting an object of a known
Finding camera pose in 3d space
A python implementation of "Multi-Camera Color Correction via Hybrid Histogram Matching"
BabelCalib: A Universal Approach to Calibrating Central Cameras. In ICCV (2021)
We will look at the role and use of calibrated cameras for simple photomosaicing.
Calculate intrinsic and extrinsic camera calibration parameters of mobile phone's camera using a checkerboard pattern object and compare the errors between the re-projected points with the original points in Matlab
In this repository, camera calibration is implemented using MATLAB Camera Calibrator APP. It is apart of Assignment2 in Sensing, Perception and Actuation course for ROCV master's program at Innopolis University.
Weekly graded projects of the "Computer Vision" course, ETH Zürich (Fall 2020).
Single-View Auto-Calibration from Lens-Distorted Images of Urban Scenes. In WACV (2021)
This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.
This repository hosts some of the important work I have accomplished within the courses of Autonomous Robotics and Visual Perception (some more complete than others)
Testing of transformation matrices between Lidar Velodyne VLP16 and RGB camera with MatLAB
This demo uses a deep neural network and two generic cameras to perform 3D pose estimation.
Computer Vision, CSE 6367, projects. Class is taken during Spring 2019, taught by Dr. William Beksi.
Computer vision project on camera calibration and other tasks
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