Open AccessApplication of Monocular Direct Vision Odometry in Augmented Reality
Author(s) -
Zuoming Zhang,
Zixuan Wang,
Hanwen Wang,
Xin Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1748/4/042049
Subject(s) - augmented reality , computer vision , artificial intelligence , visual odometry , computer science , odometry , monocular , pose , point cloud , feature (linguistics) , monocular vision , simultaneous localization and mapping , odometer , key (lock) , ransac , mobile robot , robot , image (mathematics) , linguistics , philosophy , computer security
In recent years, the unlabeled augmented reality system has been gradually applied to various mobile devices, among which stable, accurate, and fast registration is the key to realizing this function. For this technique, this paper introduces camera exposure parameters and puts the data association and pose estimation into a unified nonlinear optimization problem. Moreover, the direct monocular vision odometer is transplanted into the augmented reality system through the position adjustment module. We compare it with the traditional visual odometry method that matches the feature points. The results show that this improved method can be used to track more quickly and build a more visual semi-dense point cloud map, which can be used to support the registration and tracking of virtual objects in augmented reality.