Deterministic vs. Probabilistic Sensing Models for Geometrical Camera Coverage Modeling

A. A. Altahir, V. Asirvadam, P. Sebastian, N. H. Hamid
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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.
几何相机覆盖建模的确定性与概率感知模型
传感器网络的经典文献将传感器可探测性分为确定性感知模型和概率感知模型。然而,用于相机覆盖建模的传感模型缺乏与上述分类的适当关联。本文主要研究视觉传感器覆盖中用于表示检测的感知模型。本文综述了用于摄像机覆盖建模的传感模型分类方法,并提出了一种更适用于几何摄像机覆盖建模的传感模型分类方法。最后,本文进行了仿真,以突出所述传感模型的差异。因此,一个典型的相机放置场景被用来评估所审查的传感模型的实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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