Optimized Views Photogrammetry: Precision Analysis and A Large-scale Case Study in Qingdao

Li, Qingquan; Yu, Wenshuai

doi:10.48550/arxiv.2206.12216

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead of using low-level features, [144] turned to detect highlevel semantic information from spherical images, such as lamp posts and street signs, which are detected based on a retrained YOLO CNN network. To geo-localizing interesting targets within urban scenes to assist vehicle navigation, [6] proposed a line of bearing (LOB) based positioning method for urban street objects, e.g., road lamps, shown in Fig. 21(c).…”

Section: B Urban Modeling and Navigationmentioning

confidence: 99%

“…With the increasing demands for fine-scale modeling, such as building facades and indoor environments, recent years have witnessed explosive development of 3D reconstruction based on low-altitude unmanned aerial vehicles (UAV) [5], [6] or terrestrial mobile mapping systems (MMS) [7]. Compared with satellite and airborne-based RS platforms, these nearground platforms have the advantages of flexible instrument integration and multi-view imaging, which can record images with extremely high spatial and temporal resolutions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

3D reconstruction of spherical images: A review of techniques, applications, and prospects

Li¹,

Weng²,

You³

et al. 2023

Preprint

View full text Add to dashboard Cite

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 consumergrade 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-ofthe-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.

show abstract

Section: B Urban Modeling and Navigationmentioning

confidence: 99%