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A hierarchical inferential method for indoor scene classification

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Języki publikacji
EN
Abstrakty
EN
Indoor scene classification forms a basis for scene interaction for service robots. The task is challenging because the layout and decoration of a scene vary considerably. Previous studies on knowledge-based methods commonly ignore the importance of visual attributes when constructing the knowledge base. These shortcomings restrict the performance of classification. The structure of a semantic hierarchy was proposed to describe similarities of different parts of scenes in a fine-grained way. Besides the commonly used semantic features, visual attributes were also introduced to construct the knowledge base. Inspired by the processes of human cognition and the characteristics of indoor scenes, we proposed an inferential framework based on the Markov logic network. The framework is evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.
Rocznik
Strony
839--852
Opis fizyczny
Bibliogr. 77 poz., rys., tab., wykr.
Twórcy
autor
  • School of Computer Science and Technology, Harbin Institute of Technology, No. 92 West Dazhi Street, Harbin, China
autor
  • School of Computer Science and Technology, Harbin Institute of Technology, No. 92 West Dazhi Street, Harbin, China
autor
  • School of Computer Science and Technology, Harbin Institute of Technology, No. 92 West Dazhi Street, Harbin, China
autor
  • School of Computer Science and Technology, Harbin Institute of Technology, No. 92 West Dazhi Street, Harbin, China
autor
  • School of Computer Science and Technology, Harbin Institute of Technology, No. 92 West Dazhi Street, Harbin, China
Bibliografia
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
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Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7d6fbd7c-5e3c-49e1-bd8f-9ad88c86d28b
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