A study of a recognition method for human visualization analysis

In this study, we introduce a novel statistical framework for analyzing data obtained from human visual interpretation experiments. The proposed approach is formulated on the basis of the Fermi–Dirac distribution, a well-established statistical model in physics. In our implementation, an “optotype,” analogous to that employed in ophthalmological visual acuity assessments, is first defined as the fundamental stimulus parameter. The experimental outcomes—namely, the human visual interpretation rates—are regarded as a function of this optotype. By definition, the interpretation rate approaches 100% and 0% at the upper and lower limits of the optotype range, respectively. We model this relationship using the Fermi–Dirac distribution, substituting the energy variable with the optotype. Within this framework, the two intrinsic parameters of the Fermi–Dirac function, the chemical potential and temperature, serve as effective indices for quantitatively characterizing the properties of human visual interpretation behavior.