The authors introduce a system to compute both head orientation and gaze detection from a single image. The system uses a camera with fixed parameters and requires no user calibration. Their approach to head orientation is based on a geometrical model of the human face, and is derived form morphological and physiological data. Eye gaze detection is based on a geometrical model of the human eye. Two new algorithms are introduced that require either two or three feature points to be extracted from each image. Their algorithms are robust and run in real-time on a typical PC, which makes their system useful for a large variety of needs, from driver attention monitoring to machine-human interaction. The paper is organized as follows. In section 2, they present the face model that they use and how this model leads to the computation of the Euclidean face 3D orientation and position. They present simulations, which show the results are robust to error in both the model and the measurements. Section 3 introduces the overall system, combining head orientation computation and gaze detection. Section 3.4 focuses on a two-eye algorithm for gaze detection, while section 3.5 presents an alternative algorithm allowing the use of a single eye for gaze detection. This alternative may be used either on its own or in interaction with the whole system. An integrated system using both approaches is introduced in section 3.6. Finally, section 4 presents some experiments.


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    Title :

    Single image face orientation and gaze detection


    Additional title:

    Einzelbilderkennung von Gesichtsorientierung und Blickrichtung


    Contributors:

    Published in:

    Publication date :

    2010


    Size :

    2 Seiten, 17 Bilder, 16 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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