3D reconstruction from spherical images: A review of techniques,
applications, and prospects
- URL: http://arxiv.org/abs/2302.04495v4
- Date: Thu, 18 May 2023 01:23:40 GMT
- Title: 3D reconstruction from spherical images: A review of techniques,
applications, and prospects
- Authors: San Jiang, Yaxin Li, Duojie Weng, Kan You, Wu Chen
- Abstract summary: 3D reconstruction plays an increasingly important role in modern photogrammetric systems.
With the rapid evolution and extensive use of professional and consumer-grade spherical cameras, spherical images show great potential for the 3D modeling of urban and indoor scenes.
This research provides a thorough survey of the state-of-the-art for 3D reconstruction of spherical images in terms of data acquisition, feature detection and matching, image orientation, and dense matching.
- Score: 2.6432771146480283
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 3D reconstruction plays an increasingly important role in modern
photogrammetric systems. Conventional satellite or aerial-based remote sensing
(RS) platforms can provide the necessary data sources for the 3D reconstruction
of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned
Aerial Vehicles), 3D reconstruction in complicated situations, such as urban
canyons and indoor scenes, is challenging due to frequent tracking failures
between camera frames and high data collection costs. Recently, spherical
images have been extensively used due to the capability of recording
surrounding environments from one camera exposure. In contrast to perspective
images with limited FOV (Field of View), spherical images can cover the whole
scene with full horizontal and vertical FOV and facilitate camera tracking and
data acquisition in these complex scenes. With the rapid evolution and
extensive use of professional and consumer-grade spherical cameras, spherical
images show great potential for the 3D modeling of urban and indoor scenes.
Classical 3D reconstruction pipelines, however, cannot be directly used for
spherical images. Besides, there exist few software packages that are designed
for the 3D reconstruction of spherical images. As a result, this research
provides a thorough survey of the state-of-the-art for 3D reconstruction of
spherical images in terms of data acquisition, feature detection and matching,
image orientation, and dense matching as well as presenting promising
applications and discussing potential prospects. We anticipate that this study
offers insightful clues to direct future research.
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