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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 121–130 of 134 papers

TitleStatusHype
Geometric Multi-Model Fitting with a Convex Relaxation Algorithm—0
Planar Object Tracking in the Wild: A Benchmark—0
Automated Top View Registration of Broadcast Football Videos—0
Deep Image Homography EstimationCode1
Feature-based Recursive Observer Design for Homography Estimation—0
Homography Estimation From the Common Self-Polar Triangle of Separate Ellipses—0
Inverting RANSAC: Global Model Detection via Inlier Rate Estimation—0
Direct Structure Estimation for 3D Reconstruction—0
Robust Multiple Homography Estimation: An Ill-Solved Problem—0
Camera Intrinsic Blur Kernel Estimation: A Reliable Framework—0
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