SGLBP: Subgraph‐based Local Binary Patterns for Feature Extraction on Point Clouds

dc.contributor.authorGuo, Baoen_US
dc.contributor.authorZhang, Yuheen_US
dc.contributor.authorGao, Jianen_US
dc.contributor.authorLi, Chunhuien_US
dc.contributor.authorHu, Yaoen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2022-10-11T05:24:54Z
dc.date.available2022-10-11T05:24:54Z
dc.date.issued2022
dc.description.abstractExtraction for points that can outline the shape of a point cloud is an important task for point cloud processing in various applications. The topology information of the neighbourhood of a point usually contains sufficient information for detecting features, which is fully considered in this study. Therefore, a novel method for extracting feature points based on the topology information is proposed. First, an improved ‐shape technique is introduced, generating two graphs for potential feature detection and neighbourhood description, respectively. Local binary pattern (LBP) is then applied to the subgraphs, thus subgraph‐based local binary patterns (SGLBPs) are generated for encoding the topology of the neighbourhoods of points, which helps to remove non‐feature points from potential feature points. The proposed method can directly process raw point clouds and needs no prior surface reconstruction or geometric invariants computation; furthermore, the proposed method detects feature points by analysing the topologies of the neighbourhoods of points, consequently promoting the effectiveness for tiny features and the robustness to noises and non‐uniformly sampling patterns. The experimental results demonstrate that the proposed method is robust and achieves state‐of‐the‐art performance.en_US
dc.description.number6
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume41
dc.identifier.doi10.1111/cgf.14500
dc.identifier.issn1467-8659
dc.identifier.pages51-66
dc.identifier.urihttps://doi.org/10.1111/cgf.14500
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14500
dc.publisher© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjectCAD
dc.subjectmodelling
dc.subjectpoint‐based graphics
dc.titleSGLBP: Subgraph‐based Local Binary Patterns for Feature Extraction on Point Cloudsen_US
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