Semi-automatic Residential Floor Plan Detection: Developing a Tool for Humanities Research

Abstract

Architectural floor plans are tangible cultural history artifacts, valuable for documenting how people live, work, and recreate, both in the present and going back hundreds or even thousands of years. Today, floor plans are created using digital technologies, but prior to the 1990s, the majority were drafted by hand. For archives, the storage, conservation, and handling of hand-drawn floor plans, which are often oversized and fragile, can be challenging. The digitization of floor plans, therefore, can reduce the possibility of damage while providing greater accessibility. However, even with digitization, researchers and archives continue to encounter barriers utilizing and cataloging these collections. Manually processing, collecting, and analyzing information contained in floor plans is time-consuming and prone to human error, particularly when working with large floor plan corpora. A tool to facilitate the broader use of archival floor plans is needed. Here, we propose the Building Database and Analytics System (BuDAS), a tool for the detection, storage, and analysis of floor plan information to assist scholars' research on collections and support metadata capture. In this article, we explore the challenges of detecting floor plan information and provide an overview of BuDAS, which we developed to address these problems. In addition, we test BuDAS's room detection system on two groups of floor plans sourced from archives, representing different levels of detection difficulty. The limitations and future implications of BuDAS and floor plan detection will also be discussed.