Camera Calibration
54 papers with code • 0 benchmarks • 1 datasets
Benchmarks
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Libraries
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Cross-View Cross-Scene Multi-View Crowd Counting Dataset
Most implemented papers
Improvements to Target-Based 3D LiDAR to Camera Calibration
The homogeneous transformation between a LiDAR and monocular camera is required for sensor fusion tasks, such as SLAM.
LiDAR-Camera Calibration using 3D-3D Point correspondences
With the advent of autonomous vehicles, LiDAR and cameras have become an indispensable combination of sensors.
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
kornia/kornia
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This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems.
Sports Camera Calibration via Synthetic Data
lood339/SCCvSD
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Here we propose a highly automatic method for calibrating sports cameras from a single image using synthetic data.
Leveraging blur information for plenoptic camera calibration
This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of micro-lenses are used, using raw images only.
Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
In contrast, generic camera models allow for very accurate calibration due to their flexibility.
PlenoptiCam v1.0: A light-field imaging framework
Light-field cameras play a vital role for rich 3-D information retrieval in narrow range depth sensing applications.
Traffic Camera Calibration via Vehicle Vanishing Point Detection
kocurvik/deep_vp
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From the detected pairs of vanishing points for multiple vehicles in a scene we establish the scene geometry by estimating the focal length of the camera and the orientation of the road plane.
ChESS - Quick and Robust Detection of Chess-board Features
Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust.
Photometric Bundle Adjustment for Dense Multi-View 3D Modeling
Motivated by a Bayesian vision of the 3D multi-view reconstruction from images problem, we propose a dense 3D reconstruction technique that jointly refines the shape and the camera parameters of a scene by minimizing the photometric reprojection error between a generated model and the observed images, hence considering all pixels in the original images.
