Needle in a haystack: feasibility of identifying small safety assets from point clouds using deep learning

G. Anjanappa, S. Nikoohemat, S. Oude Elberink, R. L. Vôute, V. V. Lehtola

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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Abstract

Asset management systems are beneficial for maintaining building infrastructure and can be used to keep up-to-date records of relevant safety assets, such as smoke detectors, exit signs, and fire extinguishers. Existing methods for locating and identifying these assets in buildings primarily rely on surveys and images, which only provide 2D locations and can be tedious for large-scale structures. Indoor point clouds, which can be captured quickly for buildings using mobile scanning techniques, can provide us with 3D asset locations. In this paper, we study the feasibility of using 3D point clouds of buildings combined with deep learning techniques to identify safetyrelated assets, particularly small-sized assets like fire switches and exit signs. We adopt the state-of-the-art Deep Learning network, Kernel Point-Fully Convolutional Network (KP-FCNN), to identify these assets through semantic segmentation. Using the obtained results, we create a 3D-geometry model of the building with assets pinpointed, providing scene semantics and delivering more value. Our method is tested using three different point cloud datasets obtained from a depth camera, a mobile laser scanner, and an iPhone lidar sensor.
Original languageEnglish
Title of host publicationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Subtitle of host publicationISPRS Geospatial Week 2023
EditorsN. El-Sheimy, A.A. Abdelbary, N. El-Bendary, Y. Mohasseb
Place of PublicationCairo
PublisherCopernicus
Pages461-468
Number of pages8
VolumeX-1/W1-2023
DOIs
Publication statusPublished - 2023
EventISPRS Geospatial Week 2023 - Intercontinental Cairo Semiramis, Cairo, Egypt
Duration: 2 Sept 20237 Sept 2023

Publication series

NameISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
PublisherCopernicus
ISSN (Print)2194-9042

Conference

ConferenceISPRS Geospatial Week 2023
Country/TerritoryEgypt
CityCairo
Period2/09/237/09/23

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