Glimpse: A gaze-based measure of temporal salience
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comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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INVESTIGACIONMetadata
Title
Glimpse: A gaze-based measure of temporal salienceDate
2021-04-29Publisher
Multidisciplinary Digital Publishing InstituteISSN
1424-8220Bibliographic citation
Traver, V.J.; Zorío, J.; Leiva, L.A. GLIMPSE: A Gaze-Based Measure of Temporal Salience. Sensors 2021, 21, 3099. https://doi.org/10.3390/s21093099Type
info:eu-repo/semantics/articlePublisher version
https://www.mdpi.com/1424-8220/21/9/3099/htmVersion
info:eu-repo/semantics/publishedVersionSubject
Abstract
Temporal salience considers how visual attention varies over time. Although visual salience
has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored,
despite arguably being ... [+]
Temporal salience considers how visual attention varies over time. Although visual salience
has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored,
despite arguably being of utmost importance to understand the temporal evolution of attention
on dynamic contents. To address this gap, we proposed GLIMPSE, a novel measure to compute
temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure
is conceptually simple, training free, and provides a semantically meaningful quantification of
visual attention over time. As an extension, we explored scoring algorithms to estimate temporal
salience from spatial salience maps predicted with existing computational models. However, these
approaches generally fall short when compared with our proposed gaze-based measure. GLIMPSE
could serve as the basis for several downstream tasks such as segmentation or summarization of
videos. GLIMPSE’s software and data are publicly available. [-]
Is part of
Sensors, 21, 2021.Project code
UJI-B2018-44 | RED2018-102511-T
Project title or grant
Generación automática de resumenes de datos visuales egocéntricos | Red española de aprendizaje automático y visión artificial para el análisis de personas y la percepción robótica
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info:eu-repo/semantics/openAccess
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