Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling

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.

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Abstract

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.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 8th International Conference on Intelligent and Advanced Systems, ICIAS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:175661
Uncontrolled Keywords: Sensor networks, Camera coverage; Camera placement; Coverage models; Deterministic sensing; Deterministics; Probabilistic sensing; Probabilistic sensing models; Probabilistics; Sensing model; Sensors network, Cameras
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:30
Last Modified: 10 Nov 2023 03:30
URI: https://khub.utp.edu.my/scholars/id/eprint/15465

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