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Robotics 2016, 5(1), 8; doi:10.3390/robotics5010008

Extracting Semantic Information from Visual Data: A Survey

School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
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Author to whom correspondence should be addressed.
Academic Editor: Hong Zhang
Received: 17 December 2015 / Revised: 12 February 2016 / Accepted: 23 February 2016 / Published: 2 March 2016
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Abstract

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. View Full-Text
Keywords: semantic map; visual data; feature extraction; object recognition; place recognition; semantic representation semantic map; visual data; feature extraction; object recognition; place recognition; semantic representation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Liu, Q.; Li, R.; Hu, H.; Gu, D. Extracting Semantic Information from Visual Data: A Survey. Robotics 2016, 5, 8.

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