Autor:

Jiang,Jingzhe ; Liu, Peng ; Ye, Zhipeng ; Zhao, Wei ; Tang, Xianglong

Współtwórca:

Stefanowski, Jerzy - ed. ; Krawiec, Krzysztof - ed. ; Wrembel, Robert - ed.

Tytuł:

A hierarchical inferential method for indoor scene classification

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, Volume 27 (2017)

Temat i słowa kluczowe:

indoor scene classification ; semantic hierarchical structure ; rule-based inference ; Markov logic network

Abstract:

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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2017

Typ zasobu:

artykuł

DOI:

10.1515/amcs-2017-0059

Strony:

839-852

Źródło:

AMCS, volume 27, number 4 (2017) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego