Modelling Visuo-Haptic Perception Change in Size Estimation Tasks

TL;DR

This work studies visuo-haptic perception of size over time and reveals how perception drifts, examines the effects of visual priming and dead-reckoning, and presents a model of visuo-haptic perception as a cyclical, self- adjusting system.

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.

Figures (12)

• Figure 1: A device changes its size (width of grasp) between 6 cm and 8 cm. (a) Breakdown mechanical design of the device. The motor and gear in the centre drives the sides of the cube via the gear racks to expand/contract. (b) The contraction mode of the device with the appearance of a cube with the width of 6 cm. (c) The expansion mode of the device with the width of 8 cm. (d) The photo of the prototype (in contraction mode).
• Figure 2: The procedure includes four 6-minute estimation task blocks (an initial one and three after each acclimation game block), three 4-minute break blocks (before each acclimation game block) and three 8-minute acclimation game blocks. The overall designed study time is 60 minutes. The figure shows (a) procedure of conditions 1 and 2 without any priming and (b) procedure of condition 3 and 4 with visual priming at the beginning of the study and the beginning of the last (third) acclimation game block.
• Figure 3: Experimental setup. (a) shows the apparatus and overall setup of the physical environment. (b) and (c) are accordingly the virtual scenes of the estimation task and acclimation game.
• Figure 4: Data analysis of condition 1. (a) showcases an example of how the proportions of answers are fitted to sigmoid function and how upper detection thresholds, point of subjective equality and lower detection threshold are calculated with data of condition 1, estimation task 1. (b) plots the perception thresholds and PSE of all estimation tasks in condition 1 together with time as the horizontal axis. Fitting parameters including a, b and McFadden $R^2$ are shown alongside.
• Figure 5: Data analysis of condition 2. Plots are the perception thresholds and PSE of all estimation tasks over time in condition 2. The device performed a size-changing in hand in condition 2 between 6 cm and 8 cm (orders were randomised). And therefore, we have results for both physical sizes before and after size-changing. (a) shows results of 6 cm physical device when grasping (before changing to 8 cm in hand), and (b) shows also 6 cm physical device results but after changing from 8 cm in hand. Similarly, (c) shows results of 8 cm physical device when grasping, before changing to 6 cm, and (d) shows results of 8 cm physical device after changing from 6 cm in hand. Fitting parameters including a, b and McFadden $R^2$ are shown alongside.