Heat-map based occupancy estimation using adaptive boosting

Naser, A ORCID: https://orcid.org/0000-0001-5969-1756, Lotfi, A ORCID: https://orcid.org/0000-0002-5139-6565, Zhong, J ORCID: https://orcid.org/0000-0001-7642-2961 and He, J ORCID: https://orcid.org/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

Full text not available from this repository.

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:	Number Type 10.1109/fuzz48607.2020.9177685 DOI 1358651 Other
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

Actions (login required)

Edit View

Statistics

Views

Downloads