DEEP LEARNING FOR THREE DIMENSIONAL (3D) GAZE PREDICTION

    公开(公告)号:US20210042520A1

    公开(公告)日:2021-02-11

    申请号:US16901377

    申请日:2020-06-15

    Applicant: Tobii AB

    Abstract: There is disclosed a computer implemented eye tracking system and corresponding method and computer readable storage medium, for detecting three dimensional, 3D, gaze, by obtaining at least one head pose parameter using a head pose prediction algorithm, the head pose parameter(s) comprising one or more of a head position, pitch, yaw, or roll; and to input the at least one head pose parameter along with at least one image of a user's eye, generated from a 2D image captured using an image sensor associated with the eye tracking system, into a neural network configured to generate 3D gaze information based on the at least one head pose parameter and the at least one eye image.

    OBJECT ORIENTATION ESTIMATION
    2.
    发明公开

    公开(公告)号:US20230154030A1

    公开(公告)日:2023-05-18

    申请号:US17244852

    申请日:2021-04-29

    Applicant: Tobii AB

    CPC classification number: G06T7/70 G06T2207/20076 G06T2207/20084

    Abstract: The invention is related to a method of estimating an orientation of an object in an image, comprising the steps of: calculating, for the object in the image, a probability distribution of rotation; and estimating the orientation of the object from the calculated probability distribution; wherein the step of calculating the probability distribution and/or the step of estimating the orientation of the object are executed by a neural network; wherein the probability distribution is a matrix Fisher probability density function; and wherein the step of calculating the probability distribution includes approximating a normalizing function for the matrix Fisher probability density function.

    Determination of gaze calibration parameters

    公开(公告)号:US11169604B2

    公开(公告)日:2021-11-09

    申请号:US17099246

    申请日:2020-11-16

    Applicant: Tobii AB

    Abstract: A method for determining gaze calibration parameters for gaze estimation of a viewer using an eye-tracking system. The method comprises obtaining a set of data points including gaze tracking data of the viewer and position information of at least one target visual; selecting a first subset of the data points and determining gaze calibration parameters using said first subset. A score for the gaze calibration parameters is determined by using the gaze calibration parameters with a second subset of data points, wherein at least one data point of the subset is not included in the first subset. The score is indicative of the capability of the gaze calibration parameters to reflect position information of the at least one target visual based on the gaze tracking data. The score is compared to a candidate score and if it is higher, the calibration parameters are set to the candidate calibration parameters and the score to the candidate score.

    TRAINING OF A GAZE TRACKING MODEL
    4.
    发明申请

    公开(公告)号:US20200225745A1

    公开(公告)日:2020-07-16

    申请号:US16715219

    申请日:2019-12-16

    Applicant: Tobii AB

    Abstract: A gaze tracking model is adapted to predict a gaze ray using an image of the eye. The model is trained using training data which comprises a first image of an eye, reference gaze data indicating a gaze point towards which the eye was gazing when the first image was captured, and images of an eye captured by first and second cameras at a point in time. The training comprises forming a distance between the gaze point and a gaze ray predicted by the model using the first image, forming a consistency measure based on a gaze ray predicted by the model using the image captured by the first camera and a gaze ray predicted by the model using the image captured by the second camera, forming an objective function based on at least the formed distance and the consistency measure, and training the model using the objective function.

    Deep learning for three dimensional (3D) gaze prediction

    公开(公告)号:US11301677B2

    公开(公告)日:2022-04-12

    申请号:US16901377

    申请日:2020-06-15

    Applicant: Tobii AB

    Abstract: There is disclosed a computer implemented eye tracking system and corresponding method and computer readable storage medium, for detecting three dimensional, 3D, gaze, by obtaining at least one head pose parameter using a head pose prediction algorithm, the head pose parameter(s) comprising one or more of a head position, pitch, yaw, or roll; and to input the at least one head pose parameter along with at least one image of a user's eye, generated from a 2D image captured using an image sensor associated with the eye tracking system, into a neural network configured to generate 3D gaze information based on the at least one head pose parameter and the at least one eye image.

    DETERMINATION OF GAZE CALIBRATION PARAMETERS

    公开(公告)号:US20210173477A1

    公开(公告)日:2021-06-10

    申请号:US17099246

    申请日:2020-11-16

    Applicant: Tobii AB

    Abstract: A method for determining gaze calibration parameters for gaze estimation of a viewer using an eye-tracking system. The method comprises obtaining a set of data points including gaze tracking data of the viewer and position information of at least one target visual; selecting a first subset of the data points and determining gaze calibration parameters using said first subset. A score for the gaze calibration parameters is determined by using the gaze calibration parameters with a second subset of data points, wherein at least one data point of the subset is not included in the first subset. The score is indicative of the capability of the gaze calibration parameters to reflect position information of the at least one target visual based on the gaze tracking data. The score is compared to a candidate score and if it is higher, the calibration parameters are set to the candidate calibration parameters and the score to the candidate score.

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