Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform

Fuente: arXiv
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Main Authors: Palider, Matej, Eldardeer, Omar, Kocur, Viktor
Format: Preprint
Published: 2025
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author Palider, Matej
Eldardeer, Omar
Kocur, Viktor
author_facet Palider, Matej
Eldardeer, Omar
Kocur, Viktor
contents This paper evaluates the current gaze estimation methods within an HRI context of a shared workspace scenario. We introduce a new, annotated dataset collected with the NICO robotic platform. We evaluate four state-of-the-art gaze estimation models. The evaluation shows that the angular errors are close to those reported on general-purpose benchmarks. However, when expressed in terms of distance in the shared workspace the best median error is 16.48 cm quantifying the practical limitations of current methods. We conclude by discussing these limitations and offering recommendations on how to best integrate gaze estimation as a modality in HRI systems.
format Preprint
id arxiv_https___arxiv_org_abs_2509_24001
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform
Palider, Matej
Eldardeer, Omar
Kocur, Viktor
Computer Vision and Pattern Recognition
Robotics
I.4.9
This paper evaluates the current gaze estimation methods within an HRI context of a shared workspace scenario. We introduce a new, annotated dataset collected with the NICO robotic platform. We evaluate four state-of-the-art gaze estimation models. The evaluation shows that the angular errors are close to those reported on general-purpose benchmarks. However, when expressed in terms of distance in the shared workspace the best median error is 16.48 cm quantifying the practical limitations of current methods. We conclude by discussing these limitations and offering recommendations on how to best integrate gaze estimation as a modality in HRI systems.
title Gaze Estimation for Human-Robot Interaction: Analysis Using the NICO Platform
topic Computer Vision and Pattern Recognition
Robotics
I.4.9
url https://arxiv.org/abs/2509.24001