Lanillos, P., Ferreira, J.F. ORCID: 0000-0002-2510-2412 and Dias, J., 2017. A Bayesian hierarchy for robust gaze estimation in human–robot interaction. International Journal of Approximate Reasoning, 87, pp. 1-22. ISSN 0888-613X
|
Text
10584_Ferreira.pdf - Post-print Download (4MB) | Preview |
Abstract
In this text, we present a probabilistic solution for robust gaze estimation in the context of human–robot interaction. Gaze estimation, in the sense of continuously assessing gaze direction of an interlocutor so as to determine his/her focus of visual attention, is important in several important computer vision applications, such as the development of non-intrusive gaze-tracking equipment for psychophysical experiments in neuroscience, specialised telecommunication devices, video surveillance, human–computer interfaces (HCI) and artificial cognitive systems for human–robot interaction (HRI), our application of interest. We have developed a robust solution based on a probabilistic approach that inherently deals with the uncertainty of sensor models, but also and in particular with uncertainty arising from distance, incomplete data and scene dynamics. This solution comprises a hierarchical formulation in the form of a mixture model that loosely follows how geometrical cues provided by facial features are believed to be used by the human perceptual system for gaze estimation. A quantitative analysis of the proposed framework's performance was undertaken through a thorough set of experimental sessions. Results show that the framework performs according to the difficult requirements of HRI applications, namely by exhibiting correctness, robustness and adaptiveness.
Item Type: | Journal article | ||||||
---|---|---|---|---|---|---|---|
Publication Title: | International Journal of Approximate Reasoning | ||||||
Creators: | Lanillos, P., Ferreira, J.F. and Dias, J. | ||||||
Publisher: | Elsevier | ||||||
Date: | August 2017 | ||||||
Volume: | 87 | ||||||
ISSN: | 0888-613X | ||||||
Identifiers: |
|
||||||
Divisions: | Schools > School of Science and Technology | ||||||
Record created by: | Jonathan Gallacher | ||||||
Date Added: | 19 Mar 2018 13:44 | ||||||
Last Modified: | 19 Mar 2018 13:48 | ||||||
URI: | https://irep.ntu.ac.uk/id/eprint/33022 |
Actions (login required)
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year