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Naser, A. 
ORCID: 0000-0001-5969-1756, 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
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 | ||||||
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| 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: |
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| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Jonathan Gallacher | ||||||
| Date Added: | 01 Sep 2020 09:37 | ||||||
| Last Modified: | 02 Sep 2022 08:39 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/40603 |
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