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Methods and Applications of Space Understanding in Indoor Environment—A Decade Survey

Authors :
Sebastian Pokuciński
Dariusz Mrozek
Source :
Applied Sciences, Vol 14, Iss 10, p 3974 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The demand for digitizing manufacturing and controlling processes has been steadily increasing in recent years. Digitization relies on different techniques and equipment, which produces various data types and further influences the process of space understanding and area recognition. This paper provides an updated view of these data structures and high-level categories of techniques and methods leading to indoor environment segmentation and the discovery of its semantic meaning. To achieve this, we followed the Systematic Literature Review (SLR) methodology and covered a wide range of solutions, from floor plan understanding through 3D model reconstruction and scene recognition to indoor navigation. Based on the obtained SLR results, we identified three different taxonomies (the taxonomy of underlying data type, of performed analysis process, and of accomplished task), which constitute different perspectives we can adopt to study the existing works in the field of space understanding. Our investigations clearly show that the progress of works in this field is accelerating, leading to more sophisticated techniques that rely on multidimensional structures and complex representations, while the processing itself has become focused on artificial intelligence-based methods.

Details

Language :
English
ISSN :
14103974 and 20763417
Volume :
14
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.3f3291aa191042c2a037fc106434df76
Document Type :
article
Full Text :
https://doi.org/10.3390/app14103974