Publication | Open Access
High‐level feature aggregation for fine‐grained architectural floor plan retrieval
18
Citations
18
References
2018
Year
EngineeringSemantic SearchComputer-aided DesignHigh‐level Feature AggregationSocial SciencesText MiningImage AnalysisInformation RetrievalData ScienceArchitectural ModelArchitectural TechnologyFeature (Computer Vision)Semantic ApproachData RetrievalArchitectural Floor PlanGeometric ModelingMachine VisionDesignComputer VisionArchitectural DesignFloor PlansMassive Growth
Due to the massive growth of real estate industry, there is an increase in the number of online platforms designed for finding homes/furnished properties. Instead of descriptive words, query by example is always a preferred method for retrieval. Floor plans are the basic 2D representation giving an idea about the building structure at a particular level. The authors propose a framework for the retrieval of similar architectural floor plans under the query by example paradigm. They propose a novel algorithm to extract high‐level semantic features from an architectural floor plan. Fine‐grained retrieval using weighted sum of the features is proposed, where a feature can be given more preference over others, during retrieval. Experiments were performed on publicly available dataset containing 510 floor plans and compared with existing state‐of‐the‐art techniques. Their proposed method outperforms others both in qualitative and quantitative terms.
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