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Using semantic maps for room recognition to aid visually impaired people

Liu, Q and Li, R and Hu, H and Gu, D (2016) Using semantic maps for room recognition to aid visually impaired people. In: UNSPECIFIED, ? - ?.

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Millions of people in the world suffer from vision impairment or even vision loss. Guide sticks and dogs have been deployed to lead them around various obstacles. However, both of them are not capable of interacting with human users who normally rely on conceptual knowledge or semantic contents of the environment. This paper first builds a 3D semantic indoor environment map with an RGB-D sensor. Then, the map is used for room recognition during the revisits based on appearance by applying a convolutional neural network. Representative objects extracted from the semantic map are used to diagnose and eliminate errors during room recognition. The proposed method result in a 97.8% accuracy even with lighting condition and small object location changes.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2016 22nd International Conference on Automation and Computing, ICAC 2016: Tackling the New Challenges in Automation and Computing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 27 Feb 2017 16:31
Last Modified: 30 Mar 2021 23:15

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