Automatic analysis and sketch-based retrieval of architectural floor plans

Ahmed, Sheraz; Weber, Markus; Liwicki, Marcus; Langenhan, Christoph; Dengel, Andreas; Petzold, Frank

doi:10.1016/j.patrec.2013.04.005

Cited by 52 publications

(20 citation statements)

References 38 publications

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“…These are in the form of well-defined annotations, symbols or labels describing the functional characteristics of the space. Approaches have been proposed to aggregate this information by extracting the annotations [5] or to define this information using the geometric information and the domain knowledge [6]. Further, CAD and BIM have also evolved to define not only the boundary of these spaces but also information pertaining to the elements that occupy it like furniture, obstacles and other objects.…”

Section: Indoor Data Capturementioning

confidence: 99%

Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

Maheshwari

Srivastava

Rajan

2019

IJGI

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Geospatial data capture and handling of indoor spaces is increasing over the years and has had a varied history of data sources ranging from architectural and building drawings to indoor data acquisition approaches. While these have been more data format and information driven primarily for the physical representation of spaces, it is important to note that many applications look for the semantic information to be made available. This paper proposes a space classification model leading to an ontology for indoor spaces that accounts for both the semantic and geometric characteristics of the spaces. Further, a Space semantic model is defined, based on this ontology, which can then be used appropriately in multiple applications. To demonstrate the utility of the model, we also present an extension to the IndoorGML data standard with a set of proposed classes that can help capture both the syntactic and semantic components of the model. It is expected that these proposed classes can be appropriately harnessed for use in diverse applications ranging from indoor data visualization to more user customised building evacuation path planning with a semantic overtone.

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Section: Indoor Data Capturementioning

confidence: 99%

Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

Maheshwari

Srivastava

Rajan

2019

IJGI

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“…Recognition of online hand-drawn circuit diagrams is studied in [8] where the authors employ two-dimensional dynamic programming (2D-DP) technique to segment and recognize the symbols. Likewise, recognition of architectural drawings [1], flow charts [10], Mathematical expressions [2], UML diagrams [9] and free hand sketches [11] has also been investigated in a number of studies.…”

Section: Related Workmentioning

confidence: 99%

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Moetesum¹,

Younus²,

Warsi³

et al. 2018

ICST Transactions on Scalable Information Systems

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This paper presents an effective technique for segmentation and recognition of electronic components from hand-drawn circuit diagrams. Segmentation is carried out by using a series of morphological operations on the binarized images of circuits and discriminating between three categories of components (closed shape, components with connected lines, disconnected components). Each segmented component is characterized by computing the Histogram of Oriented Gradients (HOG) descriptor while classification is carried out using Support Vector Machine (SVM). The system is evaluated on 100 hand-drawn circuit diagrams with a total of 350 components. A segmentation accuracy of 87.7% while a classification rate of 92% is realized demonstrating the effectiveness of the proposed technique.

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“…A semantic building structure description model Semantic Fingerpint (Langenhan and Petzold, 2010) was initiated to provide a structure to idea that building floor plans can be described by abstracting the building data at the level of building, storey, and room, as well as their respective topological relationships. Based on this model, a subgraph matchingbased retrieval algorithm was proposed in (Ahmed et al, 2014), where an information extraction process of floor plans is also contained and later used in the Metis project for the graph database.…”

Section: Related Workmentioning

confidence: 99%

Thinking With Containers: A Multi-Agent Retrieval Approach for the Case-Based Semantic Search of Architectural Designs

Ayzenshtadt

Langenhan

Bukhari

et al. 2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

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To provide the retrieval of information, that can be considered useful during the design conceptualization process, with advantages of distributed artificial knowledge, an approach, that distributes retrieval-related and knowledge maintaining tasks among autonomously working and case-based self-learning agents and agent groups, can be used. In this work we present the distributed retrieval system MetisCBR for the architectural design domain, where agents work in groups (containers) on resolving of user queries built with a semantic description model Semantic Fingerprint. The main aim of our approach is to carry out a basis for a considerable retrieval tool for architects, where the combination of case-based reasoning and multi-agent methods helps to achieve valuable and helpful search results in a comprehensive building design collection.

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Automatic analysis and sketch-based retrieval of architectural floor plans

Cited by 52 publications

References 38 publications

Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

Development of an Indoor Space Semantic Model and Its Implementation as an IndoorGML Extension

Segmentation and Recognition of Electronic Components in Hand-Drawn Circuit Diagrams

Thinking With Containers: A Multi-Agent Retrieval Approach for the Case-Based Semantic Search of Architectural Designs

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