Point Cloud vs. Mesh Features for Building Interior Classification

Bassier, Maarten; Vergauwen, Maarten; Poux, Florent

doi:10.3390/rs12142224

Cited by 33 publications

(27 citation statements)

References 94 publications

(128 reference statements)

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“…Use cases range from object-scale reconstruction to city-scale reconstruction, making this technique a promising way to get 3D point clouds. However, while the reconstruction precision for middle-to large-scale applications is getting increasingly better [75], remote sensing via active sensors is still favored in several infrastructure-related industries.…”

Section: Data Capture For Cultural Sitementioning

confidence: 99%

Initial User-Centered Design of a Virtual Reality Heritage System: Applications for Digital Tourism

et al. 2020

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Reality capture allows for the reconstruction, with a high accuracy, of the physical reality of cultural heritage sites. Obtained 3D models are often used for various applications such as promotional content creation, virtual tours, and immersive experiences. In this paper, we study new ways to interact with these high-quality 3D reconstructions in a real-world scenario. We propose a user-centric product design to create a virtual reality (VR) application specifically intended for multi-modal purposes. It is applied to the castle of Jehay (Belgium), which is under renovation, to permit multi-user digital immersive experiences. The article proposes a high-level view of multi-disciplinary processes, from a needs analysis to the 3D reality capture workflow and the creation of a VR environment incorporated into an immersive application. We provide several relevant VR parameters for the scene optimization, the locomotion system, and the multi-user environment definition that were tested in a heritage tourism context.

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Section: Data Capture For Cultural Sitementioning

confidence: 99%

Initial User-Centered Design of a Virtual Reality Heritage System: Applications for Digital Tourism

et al. 2020

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“…We wish to integrate automatic 3D segmentation and classification functionalities to help users populate and enrich the system. These functionalities are currently under derivation from the research works [70][71][72][73], based on device, analytic and domain knowledge. It requires, in particular, a heritage object domain ontology obtained from standardisation works (e.g., CIDOC-CRM [74]) and in line with the conceptual data model of the HIS-PC.…”

Section: Takeaways and Research Perspectivesmentioning

confidence: 99%

A Built Heritage Information System Based on Point Cloud Data: HIS-PC

Poux

Billen

Kasprzyk

et al. 2020

IJGI

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The digital management of an archaeological site requires to store, organise, access and represent all the information that is collected on the field. Heritage building information modelling, archaeological or heritage information systems now tend to propose a common framework where all the materials are managed from a central database and visualised through a 3D representation. In this research, we offer the development of a built heritage information system prototype based on a high-resolution 3D point cloud data set. The particularity of the approach is to consider a user-centred development methodology while avoiding meshing/down-sampling operations. The proposed system is initiated by a close collaboration between multi-modal users (managers, visitors, curators) and a development team (designers, developers, architects). The developed heritage information system permits the management of spatial and temporal information, including a wide range of semantics using relational along with NoSQL databases. The semantics used to describe the artifacts are subject to conceptual modelling. Finally, the system proposes a bi-directional communication with a 3D interface able to stream massive point clouds, which is a big step forward to provide a comprehensive site representation for stakeholders while minimising modelling costs.

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“…Additional features, like segment shape and size, may also be useful to separate classes. We distinguish in this paper between local features and contextual features, and we refer the reader to the paper (Bassier et al, 2020) for an extended analysis on the impact of features.…”

Section: Segment-based Feature Extractionmentioning

confidence: 99%

Unsupervised Segmentation of Indoor 3d Point Cloud: Application to Object-Based Classification

Poux

Mattes

Kobbelt

2020

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

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Abstract. Point cloud data of indoor scenes is primarily composed of planar-dominant elements. Automatic shape segmentation is thus valuable to avoid labour intensive labelling. This paper provides a fully unsupervised region growing segmentation approach for efficient clustering of massive 3D point clouds. Our contribution targets a low-level grouping beneficial to object-based classification. We argue that the use of relevant segments for object-based classification has the potential to perform better in terms of recognition accuracy, computing time and lowers the manual labelling time needed. However, fully unsupervised approaches are rare due to a lack of proper generalisation of user-defined parameters. We propose a self-learning heuristic process to define optimal parameters, and we validate our method on a large and richly annotated dataset (S3DIS) yielding 88.1% average F1-score for object-based classification. It permits to automatically segment indoor point clouds with no prior knowledge at commercially viable performance and is the foundation for efficient indoor 3D modelling in cluttered point clouds.

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Point Cloud vs. Mesh Features for Building Interior Classification

Cited by 33 publications

References 94 publications

Initial User-Centered Design of a Virtual Reality Heritage System: Applications for Digital Tourism

Initial User-Centered Design of a Virtual Reality Heritage System: Applications for Digital Tourism

A Built Heritage Information System Based on Point Cloud Data: HIS-PC

Unsupervised Segmentation of Indoor 3d Point Cloud: Application to Object-Based Classification

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