Extracting Semantic Information from Visual Data: A Survey

The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. T...

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Bibliographic Details
Main Authors:	Qiang Liu, Ruihao Li, Huosheng Hu, Dongbing Gu
Format:	Article
Language:	English
Published:	MDPI AG 2016-03-01
Series:	Robotics
Subjects:	semantic map visual data feature extraction object recognition place recognition semantic representation
Online Access:	http://www.mdpi.com/2218-6581/5/1/8

id	doaj-2797477a229a4fa794d76c235c19a244
record_format	Article
spelling	doaj-2797477a229a4fa794d76c235c19a2442020-11-24T20:51:02ZengMDPI AGRobotics2218-65812016-03-0151810.3390/robotics5010008robotics5010008Extracting Semantic Information from Visual Data: A SurveyQiang Liu0Ruihao Li1Huosheng Hu2Dongbing Gu3School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UKSchool of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UKSchool of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UKSchool of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UKThe traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.http://www.mdpi.com/2218-6581/5/1/8semantic mapvisual datafeature extractionobject recognitionplace recognitionsemantic representation
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Qiang Liu Ruihao Li Huosheng Hu Dongbing Gu
spellingShingle	Qiang Liu Ruihao Li Huosheng Hu Dongbing Gu Extracting Semantic Information from Visual Data: A Survey Robotics semantic map visual data feature extraction object recognition place recognition semantic representation
author_facet	Qiang Liu Ruihao Li Huosheng Hu Dongbing Gu
author_sort	Qiang Liu
title	Extracting Semantic Information from Visual Data: A Survey
title_short	Extracting Semantic Information from Visual Data: A Survey
title_full	Extracting Semantic Information from Visual Data: A Survey
title_fullStr	Extracting Semantic Information from Visual Data: A Survey
title_full_unstemmed	Extracting Semantic Information from Visual Data: A Survey
title_sort	extracting semantic information from visual data: a survey
publisher	MDPI AG
series	Robotics
issn	2218-6581
publishDate	2016-03-01
description	The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.
topic	semantic map visual data feature extraction object recognition place recognition semantic representation
url	http://www.mdpi.com/2218-6581/5/1/8
work_keys_str_mv	AT qiangliu extractingsemanticinformationfromvisualdataasurvey AT ruihaoli extractingsemanticinformationfromvisualdataasurvey AT huoshenghu extractingsemanticinformationfromvisualdataasurvey AT dongbinggu extractingsemanticinformationfromvisualdataasurvey
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Extracting Semantic Information from Visual Data: A Survey

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