From Gaze to Focus of Attention Export

@inproceedings{citeulike:3781436, abstract = {Identifying human gaze or eye-movement ultimately serves the purpose of identifying an individual's focus of attention. The knowledge of a person's object of interest helps us effectively communicate with other humans by allowing us to identify our conversants ' interests, state of mind, and/or intentions. In this paper we propose to track focus of attention of several participants in a meeting. Attention does not necessarily coincide with gaze, as it is a perceptual variable, as opposed to a physical one (eye or head positioning). Automatic tracking focus of attention is therefore achieved by modeling both, the persons head movements as well as the relative locations of probable targets of interest in a room. Over video sequences taken in a meeting situation, the focus of attention could be identified up to 98 \% of the time. 1.}, author = {Stiefelhagen, Rainer and Finke, Michael and Yang, Jie and Waibel, Alex}, booktitle = {Proceedings of Workshop on Perceptual User Interfaces: PUI 98}, citeulike-article-id = {3781436}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.8681}, keywords = {access, eye-gaze, perception, vision, visual-perceptual}, pages = {25--30}, posted-at = {2009-09-03 13:44:08}, priority = {2}, title = {From Gaze to Focus of Attention}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.8681}, volume = {1614}, year = {1999} }

TY - CONF ID - citeulike:3781436 L3 - citeulike-article-id:3781436 N2 - Identifying human gaze or eye-movement ultimately serves the purpose of identifying an individual's focus of attention. The knowledge of a person's object of interest helps us effectively communicate with other humans by allowing us to identify our conversants ' interests, state of mind, and/or intentions. In this paper we propose to track focus of attention of several participants in a meeting. Attention does not necessarily coincide with gaze, as it is a perceptual variable, as opposed to a physical one (eye or head positioning). Automatic tracking focus of attention is therefore achieved by modeling both, the persons head movements as well as the relative locations of probable targets of interest in a room. Over video sequences taken in a meeting situation, the focus of attention could be identified up to 98 % of the time. 1. EP - 30 TI - From Gaze to Focus of Attention VL - 1614 T2 - Proceedings of Workshop on Perceptual User Interfaces: PUI 98 SP - 25 KW - access KW - eye-gaze KW - perception KW - vision KW - visual-perceptual AU - Stiefelhagen, Rainer AU - Finke, Michael AU - Yang, Jie AU - Waibel, Alex PY - 1999/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.8681 ER -