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1.发明授权公开(公告)号：US11934955B2
公开(公告)日：2024-03-19
申请号：US18051296
申请日：2022-10-31
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Niranjan Avadhanam , Nishant Puri , Shagan Sah , Rajath Shetty , Sujay Yadawadkar , Pavlo Molchanov
IPC: G06N3/08 , G06F18/21 , G06F18/214 , G06N20/00 , G06V10/764 , G06V10/774 , G06V10/82 , G06V10/94 , G06V20/59 , G06V20/64 , G06V40/16 , G06V40/18
CPC classification number: G06N3/08 , G06F18/214 , G06F18/2193 , G06N20/00 , G06V10/764 , G06V10/774 , G06V10/82 , G06V10/95 , G06V20/597 , G06V20/647 , G06V40/171 , G06V40/193
Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.
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公开(公告)号：US20220026987A1
公开(公告)日：2022-01-27
申请号：US17498353
申请日：2021-10-11
Applicant: Nvidia Corporation
Inventor： Feng Hu , Niranjan Avadhanam , Yuzhuo Ren , Sujay Yadawadkar , Sakthivel Sivaraman , Hairong Jiang , Siyue Wu
Abstract: Apparatuses, systems, and techniques are described to determine locations of objects using images including digital representations of those objects. In at least one embodiment, a gaze of one or more occupants of a vehicle is determined independently of a location of one or more sensors used to detect those occupants.
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3.发明公开公开(公告)号：US20240143072A1
公开(公告)日：2024-05-02
申请号：US18410801
申请日：2024-01-11
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Sujay Yadawadkar , Hairong Jiang , Nishant Puri , Niranjan Avadhanam
CPC classification number: G06F3/013 , G06F18/2148 , G06F18/2178 , G06V10/462 , G06V20/597 , G06V40/165 , G06V40/171
Abstract: In various examples, systems and methods are disclosed that provide highly accurate gaze predictions that are specific to a particular user by generating and applying, in deployment, personalized calibration functions to outputs and/or layers of a machine learning model. The calibration functions corresponding to a specific user may operate on outputs (e.g., gaze predictions from a machine learning model) to provide updated values and gaze predictions. The calibration functions may also be applied one or more last layers of the machine learning model to operate on features identified by the model and provide values that are more accurate. The calibration functions may be generated using explicit calibration methods by instructing users to gaze at a number of identified ground truth locations within the interior of the vehicle. Once generated, the calibration functions may be modified or refined through implicit gaze calibration points and/or regions based on gaze saliency maps.
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4.发明授权公开(公告)号：US11487968B2
公开(公告)日：2022-11-01
申请号：US17004252
申请日：2020-08-27
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Niranjan Avadhanam , Nishant Puri , Shagan Sah , Rajath Shetty , Sujay Yadawadkar , Pavlo Molchanov
Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.
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5.发明申请公开(公告)号：US20230078171A1
公开(公告)日：2023-03-16
申请号：US18051296
申请日：2022-10-31
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Niranjan Avadhanam , Nishant Puri , Shagan Sah , Rajath Shetty , Sujay Yadawadkar , Pavlo Molchanov
Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20220300072A1
公开(公告)日：2022-09-22
申请号：US17206585
申请日：2021-03-19
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Sujay Yadawadkar , Hairong Jiang , Nishant Puri , Niranjan Avadhanam
Abstract: In various examples, systems and methods are disclosed that provide highly accurate gaze predictions that are specific to a particular user by generating and applying, in deployment, personalized calibration functions to outputs and/or layers of a machine learning model. The calibration functions corresponding to a specific user may operate on outputs (e.g., gaze predictions from a machine learning model) to provide updated values and gaze predictions. The calibration functions may also be applied one or more last layers of the machine learning model to operate on features identified by the model and provide values that are more accurate. The calibration functions may be generated using explicit calibration methods by instructing users to gaze at a number of identified ground truth locations within the interior of the vehicle. Once generated, the calibration functions may be modified or refined through implicit gaze calibration points and/or regions based on gaze saliency maps.
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公开(公告)号：US11144754B2
公开(公告)日：2021-10-12
申请号：US16544442
申请日：2019-08-19
Applicant: Nvidia Corporation
Inventor： Feng Hu , Niranjan Avadhanam , Yuzhuo Ren , Sujay Yadawadkar , Sakthivel Sivaraman , Hairong Jiang , Siyue Wu
Abstract: Apparatuses, systems, and techniques are described to determine locations of objects using images including digital representations of those objects. In at least one embodiment, a gaze of one or more occupants of a vehicle is determined independently of a location of one or more sensors used to detect those occupants.
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公开(公告)号：US12236351B2
公开(公告)日：2025-02-25
申请号：US18497501
申请日：2023-10-30
Applicant: Nvidia Corporation
Inventor： Feng Hu , Niranjan Avadhanam , Yuzhuo Ren , Sujay Yadawadkar , Sakthivel Sivaraman , Hairong Jiang , Siyue Wu
IPC: G06N3/084 , G06F3/01 , G06F18/21 , G06N3/08 , G06V10/764 , G06V10/82 , G06V20/59 , G06V40/18 , G06V40/19
Abstract: Apparatuses, systems, and techniques are described to determine locations of objects using images including digital representations of those objects. In at least one embodiment, a gaze of one or more occupants of a vehicle is determined independently of a location of one or more sensors used to detect those occupants.
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9.发明公开公开(公告)号：US20240265254A1
公开(公告)日：2024-08-08
申请号：US18605628
申请日：2024-03-14
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Niranjan Avadhanam , Nishant Puri , Shagan Sah , Rajath Shetty , Sujay Yadawadkar , Pavlo Molchanov
IPC: G06N3/08 , G06F18/21 , G06F18/214 , G06N20/00 , G06V10/764 , G06V10/774 , G06V10/82 , G06V10/94 , G06V20/59 , G06V20/64 , G06V40/16 , G06V40/18
CPC classification number: G06N3/08 , G06F18/214 , G06F18/2193 , G06N20/00 , G06V10/764 , G06V10/774 , G06V10/82 , G06V10/95 , G06V20/597 , G06V20/647 , G06V40/171 , G06V40/193
Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.
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10.发明授权公开(公告)号：US11886634B2
公开(公告)日：2024-01-30
申请号：US17206585
申请日：2021-03-19
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Sujay Yadawadkar , Hairong Jiang , Nishant Puri , Niranjan Avadhanam
CPC classification number: G06F3/013 , G06F18/2148 , G06F18/2178 , G06V10/462 , G06V20/597 , G06V40/165 , G06V40/171
Abstract: In various examples, systems and methods are disclosed that provide highly accurate gaze predictions that are specific to a particular user by generating and applying, in deployment, personalized calibration functions to outputs and/or layers of a machine learning model. The calibration functions corresponding to a specific user may operate on outputs (e.g., gaze predictions from a machine learning model) to provide updated values and gaze predictions. The calibration functions may also be applied one or more last layers of the machine learning model to operate on features identified by the model and provide values that are more accurate. The calibration functions may be generated using explicit calibration methods by instructing users to gaze at a number of identified ground truth locations within the interior of the vehicle. Once generated, the calibration functions may be modified or refined through implicit gaze calibration points and/or regions based on gaze saliency maps.
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