Journal ArticleDOI
CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool
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TLDR
This paper presents a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations and implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner.Abstract:
Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research.read more
Citations
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Journal ArticleDOI
Data-driven floor plan understanding in rural residential buildings via deep recognition
TL;DR: A new framework for parsing floor plans of rural residence that combines semantic neural networks with a post-processed room segmentation is presented that has been tested on both urban and rural datasets and demonstrates efficiency and robustness compared with the state-of-the-art methods.
Journal ArticleDOI
Feasibility of Using Grammars to Infer Room Semantics
TL;DR: This work takes the research buildings at universities as examples and creates a constrained attribute grammar to represent the spatial distribution characteristics of different room types as well as the topological relations among them and proposes a bottom-up approach to construct a parse forest and infer the room type.
Journal ArticleDOI
Automatic floor plan analysis and recognition
TL;DR: In this article , the authors provide a critical revision of the methodologies and tools from rule-based and learning-based approaches between the years 1995 to 2021, and conclude that most research relies on a particular plan style, facing problems regarding generalization and comparison due to the lack of a standard metric and limited public datasets.
Proceedings ArticleDOI
Text Recognition and Classification in Floor Plan Images
TL;DR: This paper presents a method for text recognition in floor plan images and compares traditional text detection methods, based on image processing techniques, with recent approaches relying on convolutional neural networks.
Journal ArticleDOI
SUGAMAN: describing floor plans for visually impaired by annotation learning and proximity-based grammar
TL;DR: In this paper, the authors propose a framework called Sugaman (Supervised and Unified framework using Grammar and Annotation Model for Access and Navigation) for describing a floor plan and giving direction for obstacle-free movement within a building.
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Satoshi Suzuki,Keiichi Abe +1 more
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