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Content Provider | IEEE Xplore Digital Library |
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Author | Borji, A. Sihite, D.N. Itti, L. |
Copyright Year | 2012 |
Description | Author affiliation: Department of Computer Science, University of Southern California, Los Angeles, USA (Borji, A.; Sihite, D.N.; Itti, L.) |
Abstract | A large number of studies have been reported on top-down influences of visual attention. However, less progress have been made in understanding and modeling its mechanisms in real-world tasks. In this paper, we propose an approach for learning spatial attention taking into account influences of physical actions on top-down attention. For this purpose, we focus on interactive visual environments (video games) which are modest real-world simulations, where a player has to attend to certain aspects of visual stimuli and perform actions to achieve a goal. The basic idea is to learn a mapping from current mental state of the game player, represented by past actions and observations, to its gaze fixation. A data-driven approach is followed where we train a model from the data of some players and test it over a new subject. In particular, two contributions this paper makes are: 1) employing multi-modal information including mean eye position, gist of a scene, physical actions, bottom-up saliency, and tagged events for state representation and 2) analysis of different methods of combining bottom-up and top-down influences. Comparing with other top-down task-driven and bottom-up spatio-temporal models, our approach shows higher NSS scores in predicting eye positions. |
Starting Page | 444 |
Ending Page | 450 |
File Size | 1293965 |
Page Count | 7 |
File Format | |
ISBN | 9781467314039 |
ISSN | 10504729 |
e-ISBN | 9781467314053 |
e-ISBN | 9781467314046 |
DOI | 10.1109/ICRA.2012.6224551 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-05-14 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Games Wheels Vectors Visualization Computational modeling Predictive models Humans |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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