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Homography Estimation

Homography estimation is a technique used in computer vision and image processing to find the relationship between two images of the same scene, but captured from different viewpoints. It is used to align images, correct for perspective distortions, or perform image stitching. In order to estimate the homography, a set of corresponding points between the two images must be found, and a mathematical model must be fit to these points. There are various algorithms and techniques that can be used to perform homography estimation, including direct methods, RANSAC, and machine learning-based approaches.

Papers

Showing 91100 of 134 papers

TitleStatusHype
Homography Estimation with Convolutional Neural Networks Under Conditions of Variance0
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation0
HSolo: Homography from a single affine aware correspondence0
Insights into the robustness of control point configurations for homography and planar pose estimation0
Inverting RANSAC: Global Model Detection via Inlier Rate Estimation0
Localization of Ice-Rink for Broadcast Hockey Videos0
LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation0
Medical Image Analysis using Deep Relational Learning0
Noisy One-point Homographies are Surprisingly Good0
Nonlinear constructive observer design for direct homography estimation0
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