Individual Variability and Threshold Dynamics in Distance Estimation: A Statistical Analysis of Visual Perception in Built Environments

Pourbakht, Mojtaba; Kametani, Yoshihiro

doi:10.22059/jcss.2025.391801.1134

Individual Variability and Threshold Dynamics in Distance Estimation: A Statistical Analysis of Visual Perception in Built Environments

Articles in Press

Document Type : Original article

Authors

Department of Environmental and Urban Engineering, Kansai University, Osaca, Japan.

10.22059/jcss.2025.391801.1134

Abstract

Background: Understanding how humans perceive and estimate distances in built environments is critical not only for advancing perceptual psychology but also for informing the design of computational models in computer vision, robotics, and architectural design.
Aims: This study investigates the mechanisms and limitations of human distance estimation within a controlled architectural environment.
Methodology: While some previous experiments focused on estimating distances in virtual settings, the current study examines real-world estimation accuracy across a series of predefined points within an unobstructed corridor. Participants were asked to visually estimate the distance between their position and seven distinct target locations, ranging from near to far without the aid of physical reference cues. The core objective was not simply to measure accuracy, but to identify the perceptual threshold beyond which estimation errors significantly increase. A one-way ANOVA model was employed to assess the influence of variables such as actual distance and participant age on perceptual accuracy.
Results: Results revealed a consistent estimation performance up to approximately 2 m, beyond which the margin of error grew increasingly pronounced. Notably, a critical threshold was identified at 7.476 m, where estimation errors sharply escalated. The maximum observed discrepancy occurred at a distance of 10.186 m, suggesting a cognitive boundary in spatial awareness.
Conclusion: These findings contribute to the understanding of visual-spatial perception mechanisms and offer theoretical insights relevant to applications in robotics, image processing, virtual reality, and navigation system design.

Keywords

Main Subjects

computer science & technology

References

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