Modelling Visuo-Haptic Perception Change in Size Estimation Tasks

2026-03-03

AI Summary

This study investigates the dynamic interplay of visual and haptic cues in human size estimation when these sensory inputs are decoupled. Through a psychophysical experiment (N=80) combining controlled multisensory stimulation with quantitative behavioral analysis, the work presents the first computational model framing visuo-haptic perception as a recurrent adaptive system. The model elucidates the synergistic mechanisms underlying perceptual drift, visual priming effects, and haptic path integration. It successfully reproduces and predicts cross-modal perceptual biases, thereby confirming the temporal dynamics inherent in multisensory integration. These findings not only advance theoretical understanding of perceptual processes but also offer a principled computational framework for designing sensory illusions and enhancing human–computer interaction in virtual reality environments.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Computer Vision: Multi-modal Vision

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

Tangible interactions involve multiple sensory cues, enabling the accurate perception of object properties, such as size. Research has shown, however, that if we decouple these cues (for example, by altering the visual cue), then the resulting discrepancies present new opportunities for interactions. Perception over time though, not only relies on momentary sensory cues, but also on a priori beliefs about the object, implying a continuing update cycle. This cycle is poorly understood and its impact on interaction remains unknown. We study (N=80) visuo-haptic perception of size over time and (a) reveal how perception drifts, (b) examine the effects of visual priming and dead-reckoning, and (c) present a model of visuo-haptic perception as a cyclical, self-adjusting system. Our work has a direct impact on illusory perception in VR, but also sheds light on how our visual and haptic systems cooperate and diverge.

Problem

• visuo-haptic perception
• size estimation
• perceptual drift
• sensory integration
• multisensory interaction

Innovation

• visuo-haptic perception
• perceptual drift
• sensory integration
• visual priming
• self-adjusting system