Abstract
Modeling the user's attention is useful for responsive and interactive systems. This paper proposes a method for establishing joint visual attention between an experimenter and an intelligent agent. A rapid procedure is described to track the 3D head pose of the experimenter, which is used to approximate the gaze direction. The head is modeled with a sparse grid of points sampled from the surface of a cylinder. We then propose to employ a bottom-up saliency model to single out interesting objects in the neighborhood of the estimated focus of attention. We report results on a series of experiments, where a human experimenter looks at objects placed at different locations of the visual field, and the proposed algorithm is used to locate target objects automatically. Our results indicate that the proposed approach achieves high localization accuracy and thus constitutes a useful tool for the construction of natural human-computer interfaces.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 |
| DOIs | |
| Publication status | Published - 2009 |
| Externally published | Yes |
| Event | 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 - Amsterdam, Netherlands Duration: Sep 10 2009 → Sep 12 2009 |
Other
| Other | 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 |
|---|---|
| Country | Netherlands |
| City | Amsterdam |
| Period | 9/10/09 → 9/12/09 |
Fingerprint
Keywords
- Gaze estimation
- Head pose estimation
- Intelligent interaction
- Joint attention modeling
- Saliency
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
- Software
Cite this
Resolution of focus of attention using gaze direction estimation and saliency computation. / Yucel, Zeynep; Salah, Albert Ali.
Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. 2009. 5349547.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Resolution of focus of attention using gaze direction estimation and saliency computation
AU - Yucel, Zeynep
AU - Salah, Albert Ali
PY - 2009
Y1 - 2009
N2 - Modeling the user's attention is useful for responsive and interactive systems. This paper proposes a method for establishing joint visual attention between an experimenter and an intelligent agent. A rapid procedure is described to track the 3D head pose of the experimenter, which is used to approximate the gaze direction. The head is modeled with a sparse grid of points sampled from the surface of a cylinder. We then propose to employ a bottom-up saliency model to single out interesting objects in the neighborhood of the estimated focus of attention. We report results on a series of experiments, where a human experimenter looks at objects placed at different locations of the visual field, and the proposed algorithm is used to locate target objects automatically. Our results indicate that the proposed approach achieves high localization accuracy and thus constitutes a useful tool for the construction of natural human-computer interfaces.
AB - Modeling the user's attention is useful for responsive and interactive systems. This paper proposes a method for establishing joint visual attention between an experimenter and an intelligent agent. A rapid procedure is described to track the 3D head pose of the experimenter, which is used to approximate the gaze direction. The head is modeled with a sparse grid of points sampled from the surface of a cylinder. We then propose to employ a bottom-up saliency model to single out interesting objects in the neighborhood of the estimated focus of attention. We report results on a series of experiments, where a human experimenter looks at objects placed at different locations of the visual field, and the proposed algorithm is used to locate target objects automatically. Our results indicate that the proposed approach achieves high localization accuracy and thus constitutes a useful tool for the construction of natural human-computer interfaces.
KW - Gaze estimation
KW - Head pose estimation
KW - Intelligent interaction
KW - Joint attention modeling
KW - Saliency
UR - http://www.scopus.com/inward/record.url?scp=77949408954&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77949408954&partnerID=8YFLogxK
U2 - 10.1109/ACII.2009.5349547
DO - 10.1109/ACII.2009.5349547
M3 - Conference contribution
SN - 9781424447992
BT - Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009
ER -