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International Journal of Computer Vision

Erschienen in:

01.05.2014

Visual Focus of Attention in Non-calibrated Environments using Gaze Estimation

verfasst von: Stylianos Asteriadis, Kostas Karpouzis, Stefanos Kollias

Erschienen in: International Journal of Computer Vision | Ausgabe 3/2014

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Abstract

Estimating the focus of attention of a person highly depends on her/his gaze directionality. Here, we propose a new method for estimating visual focus of attention using head rotation, as well as fuzzy fusion of head rotation and eye gaze estimates, in a fully automatic manner, without the need for any special hardware or a priori knowledge regarding the user, the environment or the setup. Instead, we propose a system aimed at functioning under unpretending conditions, only with the usage of simple hardware, like a normal web-camera. Our system is aimed at functioning in a human-computer interaction environment, considering a person is facing a monitor with a camera adjusted on top. To this aim, we propose in this paper two novel techniques, based on local and appearance information, estimating head rotation, and we adaptively fuse them in a common framework. The system is able to recognize head rotational movement, under translational movements of the user towards any direction, without any knowledge or a-priori estimate of the user’s distance from the camera or camera intrinsic parameters.

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Here, saturation is used, although different color channels (or combinations) can be used

\(E'_{0}\) and \(M'_{0}\) are the coordinates of \(E_{0}\) and \(M_{0}\), translated on the second frame so that \(C_{0}\) coincides with \(C_{1}\). This has been done, in order for a visual explanation of Eqs. 8 and 9 to be given.

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Titel: Visual Focus of Attention in Non-calibrated Environments using Gaze Estimation
verfasst von: Stylianos Asteriadis
Kostas Karpouzis
Stefanos Kollias
Publikationsdatum: 01.05.2014
Verlag: Springer US
Erschienen in: International Journal of Computer Vision / Ausgabe 3/2014
Print ISSN: 0920-5691
Elektronische ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-013-0691-3

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