Camera Calibration
99 papers with code • 0 benchmarks • 3 datasets
Camera calibration involves estimating camera parameters(including camera intrinsics and extrinsics) to infer geometric features from captured sequences, which is crucial for computer vision and robotics. Driven by different architectures of the neural network, the researchers have developed two main paradigms for learning-based camera calibration and its applications. One is Regression-based Calibration，Reconstruction-based Calibration is another.
Benchmarks
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Libraries
Use these libraries to find Camera Calibration models and implementations
DeepSportRadar-v1
Cross-View Cross-Scene Multi-View Crowd Counting Dataset
CVGL
Most implemented papers
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.
Camera Calibration through Camera Projection Loss
thanif/CPL
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To the best of our knowledge, ours is the first method to jointly estimate both the intrinsic and extrinsic parameters via a multi-task learning methodology that combines analytical equations in learning framework for the estimation of camera parameters.
Multi-task Learning for Camera Calibration
thanif/CPL
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As far as we are aware, our approach is the first one that uses an approach to multi-task learning that includes mathematical formulas in a framework for learning to estimate camera parameters to predict both the extrinsic and intrinsic parameters jointly.
SoccerNet 2023 Challenges Results
lRomul/ball-action-spotting
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More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.
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.
Improved wide-angle, fisheye and omnidirectional camera calibration
In this paper an improved method for calibrating wide-angle, fisheye and omnidirectional imaging systems is presented.
High-Quality Depth From Uncalibrated Small Motion Clip
We propose a novel approach that generates a high-quality depth map from a set of images captured with a small viewpoint variation, namely small motion clip.
Lens Distortion Rectification using Triangulation based Interpolation
The method is applicable to all camera calibration methods that estimate the inverse distortion model and performs well across a large range of parameters.
Comprehensive Data Set for Automatic Single Camera Visual Speed Measurement
Camera calibration is the most crucial part of the speed measurement; therefore, we provide a brief overview of the methods and analyze a recently published method for fully automatic camera calibration and vehicle speed measurement and report the results on this data set in detail.
