Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

Sırmaçek, Beril; Shen, Yueqian; Lindenbergh, Roderik; Zlatanova, Sisi; Diakité, Abdoulaye A.

doi:10.5194/isprs-annals-iii-1-143-2016

Cited by 27 publications

(16 citation statements)

References 9 publications

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“…The selected story contains 16 million points, which is reduced to 2.1 million by subsampling. The noise is between 5 to 8 cm (technical details are in (Sirmacek et al, 2016)). The dataset in Figures 5 and 6 were acquired by a trolley system.…”

Section: Discussionmentioning

confidence: 99%

Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds

Nikoohemat

Peter

Elberink

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The use of Indoor Mobile Laser Scanners (IMLS) for data collection in indoor environments has been increasing in the recent years. These systems, unlike Terrestrial Laser Scanners (TLS), collect data along a trajectory instead of at discrete scanner positions. In this research, we propose several methods to exploit the trajectories of IMLS systems for the interpretation of point clouds. By means of occlusion reasoning and use of trajectory as a set of scanner positions, we are capable of detecting openings in cluttered indoor environments. In order to provide information about both the partitioning of the space and the navigable space, we use the voxel concept for point clouds. Furthermore, to reconstruct walls, floor and ceiling we exploit the indoor topology and plane primitives. The results show that the trajectory is a valuable source of data for feature detection and understanding of indoor MLS point clouds.

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Section: Discussionmentioning

confidence: 99%

Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds

Nikoohemat

Peter

Elberink

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…As an alternative to BIMs, many researchers concentrate on point clouds. Point clouds can be obtained relatively quickly from a variety of hand‐held devices (Diakité & Zlatanova, ; Sirmacek, Shen, Lindenbergh, Zlatanova, & Diakité, ). But since they constitute unstructured data, much effort is dedicated to their convenient spatial structuring.…”

Section: Related Workmentioning

confidence: 99%

Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding

Fichtner

Diakité

Zlatanova

et al. 2018

Transactions in GIS

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3D indoor navigation in multi-story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data.In this article we present an innovative octree-based approach for processing of 3D indoor point clouds for the purpose of multi-story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real-world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi-story indoor environments. | I NTR OD U CTI ONThe research on 3D indoor navigation is still very limited. Most of the currently available approaches use a set of 2D floor plans, which are connected via their staircases. The type and size of stairs, as well as interior obstacles such as furniture, are commonly not considered. The main reason for this is the lack of accurate and up-to-date 3D models (GIS or BIM). Point clouds of indoor environments are much more accessible, due to the growing availability of handheld or mobile 3D scanners, which allow a large building to be scanned within a few hours. This is an important quality in case of often or occasionally changing indoor environments, such as exhibition halls, museums, construction sites, or in emergency circumstances where relying on up-to-date models is essential. Additionally, the point clouds give a good Transactions in GIS. 2018;22:233-248.wileyonlinelibrary.com/journal/tgis

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“…Consequently, it is not possible to have a preview of the survey until the data come back. Moreover, the ZEB1 does not acquires any point normals and RGB information, nor either intensity unlike others range-based instruments (Sirmacek et al, 2016). Figure 5.…”

Section: Geoslam Zeb1mentioning

confidence: 99%

Testing Different Survey Techniques to Model Architectonic Narrow Spaces

Mandelli

Fassi

Perfetti

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In the architectural survey field, there has been the spread of a vast number of automated techniques. However, it is important to underline the gap that exists between the technical specification sheet of a particular instrument and its usability, accuracy and level of automation reachable in real cases scenario, especially speaking about Cultural Heritage (CH) field. In fact, even if the technical specifications (range, accuracy and field of view) are known for each instrument, their functioning and features are influenced by the environment, shape and materials of the object. The results depend more on how techniques are employed than the nominal specifications of the instruments. The aim of this article is to evaluate the real usability, for the 1:50 architectonic restitution scale, of common and not so common survey techniques applied to the complex scenario of dark, intricate and narrow spaces such as service areas, corridors and stairs of Milan's cathedral indoors. Tests have shown that the quality of the results is strongly affected by side-issues like the impossibility of following the theoretical ideal methodology when survey such spaces. The tested instruments are: the laser scanner Leica C10, the GeoSLAM ZEB1, the DOT DPI 8 and two photogrammetric setups, a full frame camera with a fisheye lens and the NCTech iSTAR, a panoramic camera. Each instrument presents advantages and limits concerning both the sensors themselves and the acquisition phase.

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Comparison of Zeb1 and Leica C10 Indoor Laser Scanning Point Clouds

Cited by 27 publications

References 9 publications

Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds

Exploiting Indoor Mobile Laser Scanner Trajectories for Semantic Interpretation of Point Clouds

Semantic enrichment of octree structured point clouds for multi‐story 3D pathfinding

Testing Different Survey Techniques to Model Architectonic Narrow Spaces

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