Dynamic indoor space reconstruction using temporal point clouds

Riku Nozaki, Masafumi Nakagawa

研究成果: Paper

抜粋

Indoor positioning, route finding, and 3D modelling are essential techniques for indoor navigation. In indoor environments, users require the suitable route based on security, safety and efficiency, because an indoor navigation would be affected by various changing objects, such as pedestrian, escalators, and doors. Therefore, an indoor navigation requires a geometrical network model to represent changing space environments to be used for walkable path estimation. A geometrical network model is generally prepared using building blueprints or CAD data. However, there are technical issues such as high operation cost, because the geometrical network model is created manually. Moreover, a manual creation is hard to represent real-time environmental changes. Therefore, we aim to develop a methodology to provide the real-time geometrical space generation using temporal point clouds. The methodology consists of a point cloud interpolation, segmentation, clustering, and labeling to represent changing objects such as pedestrian and doors. We conduct experiments on dynamic indoor space reconstruction using multi-layered laser scanner to evaluate our methodology.

元の言語English
出版物ステータスPublished - 2020 1 1
イベント40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of
継続期間: 2019 10 142019 10 18

Conference

Conference40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019
Korea, Republic of
Daejeon
期間19/10/1419/10/18

ASJC Scopus subject areas

  • Information Systems

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  • これを引用

    Nozaki, R., & Nakagawa, M. (2020). Dynamic indoor space reconstruction using temporal point clouds. 論文発表場所 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019, Daejeon, Korea, Republic of.