Survey of Architectural Floor Plan Retrieval Technology Based on 3ST Features

Feature retrieval technology for building floor plans has garnered significant attention in recent years due to its critical role in the efficient management and execution of construction projects. This paper presents a comprehensive exploration of four primary features essential for the retrieval of building floor plans: semantic features, spatial features, shape features, and texture features (collectively referred to as 3ST features). The extraction algorithms and underlying principles associated with these features are thoroughly analyzed, with a focus on advanced methods such as wavelet transforms and Fourier shape descriptors. Furthermore, the performance of various retrieval algorithms is evaluated through rigorous experimental analysis, offering valuable insights into optimizing the retrieval of building floor plans. Finally, this study outlines prospective directions for the advancement of feature retrieval technology in the context of floor plans.

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Publication Details

Journal
AI
Published
2025-03-26
DOI
https://doi.org/10.3390/ai6040067
Citations
1
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
1.28
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article

Survey of Architectural Floor Plan Retrieval Technology Based on 3ST Features

Guangsheng Luo, Xiaoyan Jiang, Hongxing Ling, Nanrun Zhou
1 citations
AI
Image Processing and 3D Reconstruction
1.28
article

Survey of Architectural Floor Plan Retrieval Technology Based on 3ST Features

Guangsheng Luo, Xiaoyan Jiang, Hongxing Ling, Nanrun Zhou
article en
1 citations

Abstract

Feature retrieval technology for building floor plans has garnered significant attention in recent years due to its critical role in the efficient management and execution of construction projects. This paper presents a comprehensive exploration of four primary features essential for the retrieval of building floor plans: semantic features, spatial features, shape features, and texture features (collectively referred to as 3ST features). The extraction algorithms and underlying principles associated with these features are thoroughly analyzed, with a focus on advanced methods such as wavelet transforms and Fourier shape descriptors. Furthermore, the performance of various retrieval algorithms is evaluated through rigorous experimental analysis, offering valuable insights into optimizing the retrieval of building floor plans. Finally, this study outlines prospective directions for the advancement of feature retrieval technology in the context of floor plans.

AIVol. 6(4)
Shanghai University of Engineering Science (CN), Shanghai Business School (CN)
Openalex Percentile: Top 22%
Image Processing and 3D Reconstruction
1.28
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