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Related Experiment Video

Updated: Jun 22, 2026

Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane

Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane

Published on: August 22, 2025

Cyclorotation models for eyes and cameras.

Miles Hansard¹, Radu Horaud

¹Institut National de Recherche en Informatique et en Automatique (INRIA) Rhône-Alpes, 38330 Montbonnot, France. miles.hansard@inrialpes.fr

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|June 27, 2009

Summary

This summary is machine-generated.

Listing's law, governing eye cyclorotation, is formulated using rotation matrices. This new model accurately predicts eye movements and aids in developing physically consistent robotic vision systems.

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Area of Science:

Ophthalmology
Robotics
Computational Neuroscience

Background:

The human visual system adheres to Listing's law, predicting eye cyclorotation based on fixation direction.
Understanding and modeling this law is crucial for accurate simulations of human vision.

Purpose of the Study:

To reformulate Listing's law using rotation matrices for a more convenient representation.
To develop and evaluate polynomial approximations of the cyclorotation function.
To enable physically consistent simulations of Listing's law for robotic vision models.

Main Methods:

Formulation of Listing's law using rotation matrices.
Derivation of the cyclorotation function within this matrix representation.
Development of two polynomial approximations for the derived function.
Numerical integration to evaluate model accuracy across various gaze directions.

Main Results:

Listing's law is effectively represented using rotation matrices.
Two polynomial approximations were developed, with the simpler one showing less than half a degree error for typical eye movements.
A method for simulating Listing's law in a physically consistent manner with calibrated images was demonstrated.

Conclusions:

The rotation matrix formulation provides a convenient and accurate way to represent Listing's law.
The developed polynomial models offer practical approximations for eye movement prediction.
This work facilitates the creation of more biologically plausible robotic models of human vision.