Heat-map based occupancy estimation using adaptive boosting

Naser, A., Lotfi, A. ORCID: 0000-0002-5139-6565, Zhong, J. ORCID: 0000-0001-7642-2961 and He, J. ORCID: 0000-0002-5616-4691, 2020. Heat-map based occupancy estimation using adaptive boosting. In: 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): 2020 conference proceedings. Piscataway, NJ: IEEE. ISBN 9781728169323

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Abstract

There is a growing demand for efficient and privacypreserving intelligent solutions in a multi-occupancy environment. This paper proposes a non-contact scheme for occupancy estimation using an infrared thermal sensor array, which has the advantages of low-cost, low-power, and high-performance capabilities. The proposed scheme offers an accurate human heat segmentation technique that extracts human body temperature from a noisy environment. It is shown that the proposed system can detect the empty occupancy state after utilising the segmentation technique with an accuracy of 100%. By using adaptive boosting, it is shown that the system is capable of measuring the non-empty occupancy with an overall accuracy of 98.2%

Item Type: Chapter in book
Description: Paper presented at the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, Scotland, 19-24 July 2020.
Creators: Naser, A., Lotfi, A., Zhong, J. and He, J.
Publisher: IEEE
Place of Publication: Piscataway, NJ
Date: 2020
ISBN: 9781728169323
Identifiers:
NumberType
10.1109/fuzz48607.2020.9177685DOI
1358651Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 01 Sep 2020 09:37
Last Modified: 01 Sep 2020 09:37
URI: http://irep.ntu.ac.uk/id/eprint/40603

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