Learning to predict where humans look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable option, models of saliency can be used to predict fixation locations. Most saliency approaches are based on bottom-up com...
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| Published in | 2009 IEEE 12th International Conference on Computer Vision pp. 2106 - 2113 |
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| Main Authors | , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.09.2009
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| Subjects | |
| Online Access | Get full text |
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| Abstract | For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable option, models of saliency can be used to predict fixation locations. Most saliency approaches are based on bottom-up computation that does not consider top-down image semantics and often does not match actual eye movements. To address this problem, we collected eye tracking data of 15 viewers on 1003 images and use this database as training and testing examples to learn a model of saliency based on low, middle and high-level image features. This large database of eye tracking data is publicly available with this paper. |
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| AbstractList | For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable option, models of saliency can be used to predict fixation locations. Most saliency approaches are based on bottom-up computation that does not consider top-down image semantics and often does not match actual eye movements. To address this problem, we collected eye tracking data of 15 viewers on 1003 images and use this database as training and testing examples to learn a model of saliency based on low, middle and high-level image features. This large database of eye tracking data is publicly available with this paper. |
| Author | Judd, Tilke Ehinger, Krista Torralba, Antonio Durand, Fredo |
| Author_xml | – sequence: 1 givenname: Tilke surname: Judd fullname: Judd, Tilke email: tjudd@mit.edu – sequence: 2 givenname: Krista surname: Ehinger fullname: Ehinger, Krista email: kehinger@mit.edu – sequence: 3 givenname: Fredo surname: Durand fullname: Durand, Fredo email: fredo@csail.mit.edu – sequence: 4 givenname: Antonio surname: Torralba fullname: Torralba, Antonio email: torralba@csail.mit.edu |
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