แนวคิดหลัก
Perceptual scale predictions from Fisher information metrics.
บทคัดย่อ
The article explores the relationship between perceptual scales and Fisher information metrics in modeling perception. It highlights the value of measuring perceptual scales for various physical variables, demonstrating their importance in probabilistic modeling of perception. The study shows that the perceptual scale is influenced by stimulus power spectrum and proposes a method to estimate perceptual geometry. Various experiments are conducted to validate predictions and explore different measurement assumptions.
สถิติ
Published as a conference paper at ICLR 2024.
ABSTRACT: Perception transforms physical variables into internal psychological variables modeled by perceptual scales.
Difference scaling methods measure relative differences in stimuli perceived color, contrast, or loudness.
MLDS infers the function mapping physical to perceptual space called perceptual scale based on Thurstone's law of comparative judgment.
Probabilistic modeling of perception integrates concepts like redundancy reduction and information maximization.
Optimal observer theory describes the relation between perceptual bias and sensitivity inspired by neural population coding models.
Fisher information quantifies variance of stimulus estimator from neural population encoding.
คำพูด
"We demonstrate the value of measuring the perceptual scale of classical and less classical physical variables."
"The main conclusion is that the perceptual scale is mostly driven by the stimulus power spectrum."
"Our work brings several contributions to overcome limitations introduced above."