SEMANTIC SEGMENTATION OF INDOOR 3D POINT CLOUDS BY JOINT OPTIMIZATION OF GEOMETRIC FEATURES AND NEURAL NETWORKS

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Abstract. Indoor navigation, indoor robotics, and other deep applications of interior space can be realized through semantic segmentation of 3D point clouds. We propose a semantic segmentation method for point clouds that uses geometric features of point clouds and neural networks to address the problem of incomplete and inconsistent segmentation objectives in existing semantic segmentation methods. Using neural networks, semantic labels are extracted from indoor structural information as the first step. The paper proposes a probabilistic model to cross-validate the initial segmentation results with the segmentation results of geometric features to achieve joint optimization of the results for semantic segmentation. Three sets of indoor point clouds data from simple to complex indoor scenes are used to test the accuracy and validity of the segmentation method proposed in this paper. The experimental results demonstrate that the method proposed in this paper can effectively improve the semantic segmentation accuracy of indoor 3D point clouds.

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: SEMANTIC SEGMENTATION OF INDOOR 3D POINT CLOUDS BY JOINT OPTIMIZATION OF GEOMETRIC FEATURES AND NEURAL NETWORKS ; volume:X-4/W2-2022 ; year:2022 ; pages:305-310 ; extent:6
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; X-4/W2-2022 (2022), 305-310 (gesamt 6)

Creator: Yao, M. M.
Li, X. M.
Wang, W. X.
Xie, L. F.
Tang, S. J.

DOI: 10.5194/isprs-annals-X-4-W2-2022-305-2022

URN: urn:nbn:de:101:1-2022102005390694791118

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:28 AM CEST

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Yao, M. M.
Li, X. M.
Wang, W. X.
Xie, L. F.
Tang, S. J.

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SEMANTIC SEGMENTATION OF INDOOR 3D POINT CLOUDS BY JOINT OPTIMIZATION OF GEOMETRIC FEATURES AND NEURAL NETWORKS

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Other Objects (12)

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