The content discusses the development of a novel camera motion estimation algorithm. It introduces the problem, presents a detailed approach to solving it, and highlights the algorithm's advantages in terms of accuracy and efficiency. The proposed method is compared with existing techniques through experiments on synthetic data.
The paper delves into the fundamental issue of inferring camera motion from 2D point correspondences in computer vision. It introduces a new measurement model based on rotation matrix and normalized translation vector for maximum likelihood estimation. The proposed two-step algorithm provides consistent estimates that converge to ground truth as point number increases, demonstrating superior performance in dense point correspondence scenarios.
Key points include:
In un'altra lingua
dal contenuto originale
arxiv.org
Approfondimenti chiave tratti da
by Guangyang Ze... alle arxiv.org 03-05-2024
https://arxiv.org/pdf/2403.01174.pdfDomande più approfondite