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公开(公告)号：US11934571B2
公开(公告)日：2024-03-19
申请号：US17039918
申请日：2020-09-30
申请人： Tobii AB
发明人： Pravin Kumar Rana , Gerald Bianchi
CPC分类号： G06F3/013 , G06T7/50 , G06T7/73 , G06T2207/30201
摘要： A system, a head-mounted device, a computer program, a carrier, and a method for a head-mounted device comprising an eye tracking sensor, for updating an eye tracking model in relation to an eye are disclosed. First sensor data in relation to the eye are obtained by means of the eye tracking sensor. After obtaining the first sensor data, the eye tracking sensor is moved in relation to the eye. After moving the eye tracking sensor, second sensor data in relation to the eye are obtained by means of the eye tracking sensor. The eye tracking model in relation to the eye is then updated based on the first sensor data and the second sensor data.
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公开(公告)号：US20230154030A1
公开(公告)日：2023-05-18
申请号：US17244852
申请日：2021-04-29
申请人： Tobii AB
发明人： David Molin , Gerald Bianchi
IPC分类号： G06T7/70
CPC分类号： G06T7/70 , G06T2207/20076 , G06T2207/20084
摘要： 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.
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公开(公告)号：US20210255698A1
公开(公告)日：2021-08-19
申请号：US17039918
申请日：2020-09-30
申请人： Tobii AB
发明人： Pravin Kumar Rana , Gerald Bianchi
摘要： A system, a head-mounted device, a computer program, a carrier, and a method for a head-mounted device comprising an eye tracking sensor, for updating an eye tracking model in relation to an eye are disclosed. First sensor data in relation to the eye are obtained by means of the eye tracking sensor. After obtaining the first sensor data, the eye tracking sensor is moved in relation to the eye. After moving the eye tracking sensor, second sensor data in relation to the eye are obtained by means of the eye tracking sensor. The eye tracking model in relation to the eye is then updated based on the first sensor data and the second sensor data.
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