Publication
From percepts to semantics: a multi-modal saliency map to support social robots’ attention
Journal Article (2025)
Journal
ACM Transactions on Human-Robot Interaction
Pages
1-19
Volume
14
Number
4
Doc link
https://doi.org/10.1145/3737891
File
Authors
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Ferrini, Lorenzo
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Andriella, Antonio
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Ros, Raquel
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Lemaignan, Séverin
Abstract
In social robots, visual attention expresses awareness of the scenario components and dynamics. As in humans, their attention focus should be driven by a combination of different attention mechanisms. In this paper, we introduce multi-modal saliency maps, i.e.
spatial representations of saliency in the world that dynamically integrate multiple sources of attention depending on the different contexts of use. We provide the mathematical formulation of the model and an open-source software implementation. Finally, we introduce initial exploration of its potential in exemplary scenarios of social situations with humans, as well as to evaluate its implementation.
Categories
intelligent robots, service robots, social aspects of automation.
Author keywords
Visual attention, Saliency, Robot gaze, Human-robot interaction
Scientific reference
L. Ferrini, A. Andriella, R. Ros and S. Lemaignan. From percepts to semantics: a multi-modal saliency map to support social robots’ attention. ACM Transactions on Human-Robot Interaction, 14(4): 1-19, 2025.

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