Heat-map based occupancy estimation using adaptive boosting

Abdallah Naser, Ahmad Lotfi, Junpei Zhong, Jun He

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

12 Citations (Scopus)


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%

Original languageEnglish
Title of host publication2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169323
Publication statusPublished - Jul 2020
Externally publishedYes
Event2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020 - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584


Conference2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020
Country/TerritoryUnited Kingdom


  • Activities of Daily Living
  • Adaptive Boosting
  • Ambient Intelligence
  • Image Segmentation
  • Independent Living
  • Multi-occupancy
  • Occupancy Estimation
  • Thermal Sensing

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics


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