Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling

Classical literature in sensor networks classifies the sensor detectability into deterministic or probabilistic sensing models. However, sensing models used in camera coverage modeling lack a proper association with respect to the aforementioned classification. This paper focuses on sensing models u...

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Main Authors: Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29197 /
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149032&doi=10.1109%2fICIAS49414.2021.9642623&partnerID=40&md5=782c0150f9197b8a4df2903ee0cc0544
http://eprints.utp.edu.my/29197/
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spelling utp-eprints.291972022-03-25T01:11:40Z Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling Altahir, A.A. Asirvadam, V.S. Sebastian, P. Hamid, N.H. Classical literature in sensor networks classifies the sensor detectability into deterministic or probabilistic sensing models. However, sensing models used in camera coverage modeling lack a proper association with respect to the aforementioned classification. This paper focuses on sensing models used to represent the detection in visual sensor coverage. The paper reviews the sensing models taxonomy used in modeling camera coverage and extrapolates a more relevant sensing model classification to be used with the geometrical camera coverage modeling. Finally, the paper carries out a simulation to highlight the variations of the reviewed sensing models. Thus, a typical camera placement scenario is used to evaluate the implementation of the reviewed sensing models. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149032&doi=10.1109%2fICIAS49414.2021.9642623&partnerID=40&md5=782c0150f9197b8a4df2903ee0cc0544 Altahir, A.A. and Asirvadam, V.S. and Sebastian, P. and Hamid, N.H. (2021) Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling. In: UNSPECIFIED. http://eprints.utp.edu.my/29197/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Classical literature in sensor networks classifies the sensor detectability into deterministic or probabilistic sensing models. However, sensing models used in camera coverage modeling lack a proper association with respect to the aforementioned classification. This paper focuses on sensing models used to represent the detection in visual sensor coverage. The paper reviews the sensing models taxonomy used in modeling camera coverage and extrapolates a more relevant sensing model classification to be used with the geometrical camera coverage modeling. Finally, the paper carries out a simulation to highlight the variations of the reviewed sensing models. Thus, a typical camera placement scenario is used to evaluate the implementation of the reviewed sensing models. © 2021 IEEE.
format Conference or Workshop Item
author Altahir, A.A.
Asirvadam, V.S.
Sebastian, P.
Hamid, N.H.
spellingShingle Altahir, A.A.
Asirvadam, V.S.
Sebastian, P.
Hamid, N.H.
Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
author_sort Altahir, A.A.
title Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
title_short Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
title_full Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
title_fullStr Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
title_full_unstemmed Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling
title_sort deterministic vs. probabilistic sensing models for geometrical camera coverage modeling
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149032&doi=10.1109%2fICIAS49414.2021.9642623&partnerID=40&md5=782c0150f9197b8a4df2903ee0cc0544
http://eprints.utp.edu.my/29197/
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score 11.62408