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公开(公告)号：US20250067581A1
公开(公告)日：2025-02-27
申请号：US18456070
申请日：2023-08-25
Applicant: NVIDIA Corporation
Inventor： Dae Jin Kim , Rajath Shetty
Abstract: In various examples, interior sensor calibration for autonomous systems and applications is described herein. Systems and methods are disclosed that may recalibrate sensors of a vehicle, such as sensors located within the interior of the vehicle, using one or more techniques. For instance, if a sensor is attached to a component within the interior of the vehicle, an additional sensor associated with the component may output data indicating the location and/or orientation of the component within the vehicle. The indicated location and/or orientation of the component may then be used to recalibrate the sensor with respect to a reference coordinate system of the vehicle. For a second example, the sensor may output data representing at least a feature located within the interior of the vehicle. The sensor may then again be recalibrated based at least on a portion of the data that represents the feature.
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2.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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3.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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4.发明授权公开(公告)号：US11688074B2
公开(公告)日：2023-06-27
申请号：US17039437
申请日：2020-09-30
Applicant: NVIDIA Corporation
Inventor： Nishant Puri , Sakthivel Sivaraman , Rajath Shetty , Niranjan Avadhanam
CPC classification number: G06T7/194 , G06F18/214 , G06F18/24 , G06N3/08 , G06T5/002 , G06T5/30 , G06V40/11 , G06V40/113 , G06T2207/20081 , G06T2207/20084 , G06T2207/20132 , G06T2207/20221 , G06T2207/30196
Abstract: In various examples, a background of an object may be modified to generate a training image. A segmentation mask may be generated and used to generate an object image that includes image data representing the object. The object image may be integrated into a different background and used for data augmentation in training a neural network. Data augmentation may also be performed using hue adjustment (e.g., of the object image) and/or rendering three-dimensional capture data that corresponds to the object from selected views. Inference scores may be analyzed to select a background for an image to be included in a training dataset. Backgrounds may be selected and training images may be added to a training dataset iteratively during training (e.g., between epochs). Additionally, early or late fusion nay be employed that uses object mask data to improve inferencing performed by a neural network trained using object mask data.
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公开(公告)号：US20240404296A1
公开(公告)日：2024-12-05
申请号：US18327643
申请日：2023-06-01
Applicant: NVIDIA Corporation
Inventor： Shagan Sah , Niranjan Avadhanam , Rajath Shetty , Ratin Kumar , Yile Chen
IPC: G06V20/58 , G06T7/20 , G06T7/50 , G06V10/764 , G06V20/59 , G08B13/196
Abstract: In various examples, low power proximity based threat detection using optical flow for vehicle systems and applications are provided. Some embodiments may use a tiered framework that uses sensor fusion techniques to detect and track the movement of a threat candidate, and perform a threat classification and/or intent prediction as the threat candidate approaches approach. Relative depth indications from optical flow, computed using data from image sensors, can be used to initially segment and track a moving object over a sequence of image frames. Additional sensors and processing may be brought online when a moving object becomes close enough to be considered a higher risk threat candidate. A threat response system may generate a risk score based on a predicted intent of a threat candidate, and when the risk score exceeds a certain threshold, then the threat response system may respond accordingly based on the threat classification and/or risk score.
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Patent Agency Ranking
公开(公告)号：US11657263B2
公开(公告)日：2023-05-23
申请号：US17005914
申请日：2020-08-28
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Hairong Jiang , Nishant Puri , Rajath Shetty , Niranjan Avadhanam
IPC: G06K9/62 , G06F18/214 , G06N20/00 , G06V10/94 , G06V20/59 , G06V20/64 , G06V40/16 , G06V40/18 , G06F18/21
CPC classification number: G06F18/214 , G06F18/2193 , G06N20/00 , G06V10/95 , G06V20/597 , G06V20/647 , G06V40/171 , G06V40/193
Abstract: Systems and methods for determining the gaze direction of a subject and projecting this gaze direction onto specific regions of an arbitrary three-dimensional geometry. In an exemplary embodiment, gaze direction may be determined by a regression-based machine learning model. The determined gaze direction is then projected onto a three-dimensional map or set of surfaces that may represent any desired object or system. Maps may represent any three-dimensional layout or geometry, whether actual or virtual. Gaze vectors can thus be used to determine the object of gaze within any environment. Systems can also readily and efficiently adapt for use in different environments by retrieving a different set of surfaces or regions for each environment.
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7.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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公开(公告)号：US20210182609A1
公开(公告)日：2021-06-17
申请号：US17005914
申请日：2020-08-28
Applicant: NVIDIA Corporation
Inventor： Nuri Murat Arar , Hairong Jiang , Nishant Puri , Rajath Shetty , Niranjan Avadhanam
Abstract: Systems and methods for determining the gaze direction of a subject and projecting this gaze direction onto specific regions of an arbitrary three-dimensional geometry. In an exemplary embodiment, gaze direction may be determined by a regression-based machine learning model. The determined gaze direction is then projected onto a three-dimensional map or set of surfaces that may represent any desired object or system. Maps may represent any three-dimensional layout or geometry, whether actual or virtual. Gaze vectors can thus be used to determine the object of gaze within any environment. Systems can also readily and efficiently adapt for use in different environments by retrieving a different set of surfaces or regions for each environment.
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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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公开(公告)号：US20240022601A1
公开(公告)日：2024-01-18
申请号：US17863140
申请日：2022-07-12
Applicant: NVIDIA Corporation
Inventor： Manoj Kumar Yennapureddy , Shagan Sah , Rajath Shetty
CPC classification number: H04L63/1466 , H04L63/1416 , G06T7/50 , G06T2207/10028 , G06T2207/20084 , G06T2207/20076
Abstract: In various examples, techniques are described for detecting whether spoofing attacks are occurring using multiple sensors. Systems and methods are disclosed that include at least a first sensor having a first pose to capture a first perspective view of a user and a second sensor having a second pose to capture a second perspective view of the user. The first sensor and/or the second sensor may include an image sensor, a depth sensor, and/or the like. The systems and methods include a neural network that is configured to analyze first sensor data generated by the first sensor and second sensor data generated by the second sensor to determine whether a spoofing attack is occurring. The systems and methods may also perform one or more processes, such as facial recognition, based on whether the spoofing attack is occurring.
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