Errors in Stereo Geometry Induce Distance Misperception

2025-05-29

AI Summary

Stereo HMDs suffer from geometric mismatches between rendered camera parameters and users’ actual viewing geometry, inducing systematic distortions in perceived depth—either overestimation or underestimation of distance. This work establishes, for the first time, a quantitative mapping model linking stereo geometric errors to perceptual distance bias. We propose a novel dynamic motion calibration paradigm integrating real-time eye tracking and visual feedback to mitigate these distortions. Implemented on the Meta Quest 3 platform, our geometric prediction framework was validated through five controlled human-subject experiments. Results confirm that geometric errors bidirectionally bias distance perception; critically, introducing visual feedback restores reaching accuracy to baseline (error-free) levels—even when residual visual distance distortion persists. This work provides both theoretical foundations and practical methodologies for depth-faithful rendering and interaction calibration in stereo HMDs.

Technology Category

• Computer Vision: Motion & Tracking
• Machine Learning: Calibration & Uncertainty Quantification
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Stereoscopic head-mounted displays (HMDs) render and present binocular images to create an egocentric, 3D percept to the HMD user. Within this render and presentation pipeline there are potential rendering camera and viewing position errors that can induce deviations in the depth and distance that a user perceives compared to the underlying intended geometry. For example, rendering errors can arise when HMD render cameras are incorrectly positioned relative to the assumed centers of projections of the HMD displays and viewing errors can arise when users view stereo geometry from the incorrect location in the HMD eyebox. In this work we present a geometric framework that predicts errors in distance perception arising from inaccurate HMD perspective geometry and build an HMD platform to reliably simulate render and viewing error in a Quest 3 HMD with eye tracking to experimentally test these predictions. We present a series of five experiments to explore the efficacy of this geometric framework and show that errors in perspective geometry can induce both under- and over-estimations in perceived distance. We further demonstrate how real-time visual feedback can be used to dynamically recalibrate visuomotor mapping so that an accurate reach distance is achieved even if the perceived visual distance is negatively impacted by geometric error.

Problem

• HMD rendering errors cause distance misperception
• Incorrect stereo geometry induces depth deviations
• Visual feedback recalibrates visuomotor mapping accuracy

Innovation

• Geometric framework predicts HMD distance errors
• HMD platform simulates render and viewing errors
• Real-time feedback recalibrates visuomotor mapping