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DC Field | Value | Language |
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dc.contributor.author | Spina, Sandro | - |
dc.contributor.author | Debattista, Kurt | - |
dc.contributor.author | Bugeja, Keith | - |
dc.contributor.author | Chalmers, A. | - |
dc.date.accessioned | 2023-02-24T13:40:10Z | - |
dc.date.available | 2023-02-24T13:40:10Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Spina, S., Debattista, K., Bugeja, K., & Chalmers, A. (2011, October). Point cloud segmentation for cultural heritage sites. In Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage, Prato. 41-48). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/106817 | - |
dc.description.abstract | Over the past few years, the acquisition of 3D point information representing the structure of real-world objects has become common practice in many areas. This is particularly true in the Cultural Heritage (CH) domain, where point clouds reproducing important and usually unique artifacts and sites of various sizes and geometric complexities are acquired. Specialized software is then usually used to process and organise this data. This paper addresses the problem of automatically organising this raw data by segmenting point clouds into meaningful subsets. This organisation over raw data entails a reduction in complexity and facilitates the post-processing effort required to work with the individual objects in the scene. This paper describes an efficient two-stage segmentation algorithm which is able to automatically partition raw point clouds. Following an intial partitioning of the point cloud, a RanSaC-based plane fitting algorithm is used in order to add a further layer of abstraction. A number of potential uses of the newly processed point cloud are presented; one of which is object extraction using point cloud queries. Our method is demonstrated on three point clouds ranging from 600K to 1.9M points. One of these point clouds was acquired from the pre-historic temple of Mnajdra consistsing of multiple adjacent complex structures. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | The Eurographics Association | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Image segmentation | en_GB |
dc.subject | Cloud computing | en_GB |
dc.subject | Megalithic temples -- Malta | en_GB |
dc.subject | Mnajdra Temples (Qrendi, Malta) | en_GB |
dc.title | Point cloud segmentation for cultural heritage sites | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | 12th International conference on Virtual Reality, Archaeology and Cultural Heritage | en_GB |
dc.bibliographicCitation.conferenceplace | Prato, Italy. 18-21/10/2011. | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
Appears in Collections: | Scholarly Works - FacICTCS |
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Point_cloud_segmentation_for_cultural_heritage_sites_2011.pdf Restricted Access | 689.22 kB | Adobe PDF | View/Open Request a copy |
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