公开(公告)号：US20220410830A1

公开(公告)日：2022-12-29

申请号：US17939613

申请日：2022-09-07

Applicant: NVIDIA Corporation

Inventor： Atousa Torabi ,  Sakthivel Sivaraman ,  Niranjan Avadhanam ,  Shagan Sah

IPC: B60R21/017 ,  B60R21/013 ,  B60W60/00 ,  G06N3/02 ,  B60W50/14

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

公开(公告)号：US20230356728A1

公开(公告)日：2023-11-09

申请号：US18144651

申请日：2023-05-08

Applicant: NVIDIA Corporation

Inventor： Anshul Jain ,  Ratin Kumar ,  Feng Hu ,  Niranjan Avadhanam ,  Atousa Torabi ,  Hairong Jiang ,  Ram Ganapathi ,  Taek Kim

IPC: B60W30/18 ,  B60W50/00 ,  B60W40/08 ,  G06V40/19 ,  G05B13/02 ,  G05D1/00 ,  G06F18/25 ,  G06V10/141 ,  G06V20/59

CPC classification number: B60W50/0098 ,  B60W30/18 ,  B60W40/08 ,  G05B13/027 ,  G05D1/0061 ,  G06F18/251 ,  G06V10/141 ,  G06V20/597 ,  G06V40/19 ,  B60W2040/0836 ,  B60W2540/26 ,  H04N23/71

Abstract: Approaches for an advanced AI-assisted vehicle can utilize an extensive suite of sensors inside and outside the vehicle, providing information to a computing platform running one or more neural networks. The neural networks can perform functions such as facial recognition, eye tracking, gesture recognition, head position, and gaze tracking to monitor the condition and safety of the driver and passengers. The system also identifies and tracks body pose and signals of people inside and outside the vehicle to understand their intent and actions. The system can track driver gaze to identify objects the driver might not see, such as cross-traffic and approaching cyclists. The system can provide notification of potential hazards, advice, and warnings. The system can also take corrective action, which may include controlling one or more vehicle subsystems, or when necessary, autonomously controlling the entire vehicle. The system can work with vehicle systems for enhanced analytics and recommendations.

公开(公告)号：US20230064049A1

公开(公告)日：2023-03-02

申请号：US17462833

申请日：2021-08-31

Applicant: Nvidia Corporation

Inventor： Sakthivel Sivaraman ,  Nishant Puri ,  Yuzhuo Ren ,  Atousa Torabi ,  Shubhadeep Das ,  Niranjan Avadhanam ,  Sumit Kumar Bhattacharya ,  Jason Roche

IPC: G06K9/00 ,  G06T7/73 ,  G06F3/01 ,  G06F16/632 ,  G06T15/06

Abstract: Interactions with virtual systems may be difficult when users inadvertently fail to provide sufficient information to proceed with their requests. Certain types of inputs, such as auditory inputs, may lack sufficient information to properly provide a response to the user. Additional information, such as image data, may enable user gestures or poses to supplement the auditory inputs to enable response generation without requesting additional information from users.

公开(公告)号：US20220012988A1

公开(公告)日：2022-01-13

申请号：US16922601

申请日：2020-07-07

Applicant: NVIDIA Corporation

Inventor： Niranjan Avadhanam ,  Sumit Bhattacharya ,  Atousa Torabi ,  Jason Conrad Roche

IPC: G08B3/10 ,  G08G1/005 ,  G06N3/08

Abstract: Systems and methods are disclosed herein for a pedestrian crossing warning system that may use multi-modal technology to determine attributes of a person and provide a warning to the person in response to a calculated risk level to effect a reduction of the risk level. The system may utilize sensors to receive data indicative of a trajectory of a person external to the vehicle. Specific attributes of the person such as age or walking aids may be determined. Based on the trajectory data and the specific attributes, a risk level may be determined by the system using a machine learning model. The system may cause emission of a warning to the person in response to the risk level.

公开(公告)号：US11851015B2

公开(公告)日：2023-12-26

申请号：US17939622

申请日：2022-09-07

Applicant: NVIDIA Corporation

Inventor： Atousa Torabi ,  Sakthivel Sivaraman ,  Niranjan Avadhanam ,  Shagan Sah

IPC: B60R21/017 ,  B60R21/013 ,  B60W60/00 ,  G06N3/02 ,  B60W50/14 ,  B60W50/00 ,  B60R21/01

CPC classification number: B60R21/017 ,  B60R21/013 ,  B60W50/14 ,  B60W60/005 ,  G06N3/02 ,  B60R2021/01211 ,  B60R2021/01286 ,  B60W2050/0062

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

公开(公告)号：US11682272B2

公开(公告)日：2023-06-20

申请号：US16922601

申请日：2020-07-07

Applicant: NVIDIA Corporation

Inventor： Niranjan Avadhanam ,  Sumit Bhattacharya ,  Atousa Torabi ,  Jason Conrad Roche

IPC: G08B3/10 ,  G06N3/08 ,  G08G1/005

CPC classification number: G08B3/10 ,  G06N3/08 ,  G08G1/005

Abstract: Systems and methods are disclosed herein for a pedestrian crossing warning system that may use multi-modal technology to determine attributes of a person and provide a warning to the person in response to a calculated risk level to effect a reduction of the risk level. The system may utilize sensors to receive data indicative of a trajectory of a person external to the vehicle. Specific attributes of the person such as age or walking aids may be determined. Based on the trajectory data and the specific attributes, a risk level may be determined by the system using a machine learning model. The system may cause emission of a warning to the person in response to the risk level.

公开(公告)号：US20230001872A1

公开(公告)日：2023-01-05

申请号：US17939622

申请日：2022-09-07

Applicant: NVIDIA Corporation

Inventor： Atousa Torabi ,  Sakthivel Sivaraman ,  Niranjan Avadhanam ,  Shagan Sah

IPC: B60R21/017 ,  B60R21/013 ,  B60W60/00 ,  G06N3/02 ,  B60W50/14

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.

公开(公告)号：US20250124734A1

公开(公告)日：2025-04-17

申请号：US18999826

申请日：2024-12-23

Applicant: Nvidia Corporation

Inventor： Sakthivel Sivaraman ,  Nishant Puri ,  Yuzhuo Ren ,  Atousa Torabi ,  Shubhadeep Das ,  Niranjan Avadhanam ,  Sumit Kumar Bhattacharya ,  Jason Roche

IPC: G06V40/10 ,  G06F3/01 ,  G06F16/632 ,  G06T7/73 ,  G06T15/06

Abstract: Interactions with virtual systems may be difficult when users inadvertently fail to provide sufficient information to proceed with their requests. Certain types of inputs, such as auditory inputs, may lack sufficient information to properly provide a response to the user. Additional information, such as image data, may enable user gestures or poses to supplement the auditory inputs to enable response generation without requesting additional information from users.

公开(公告)号：US12211308B2

公开(公告)日：2025-01-28

申请号：US17462833

申请日：2021-08-31

Applicant: Nvidia Corporation

Inventor： Sakthivel Sivaraman ,  Nishant Puri ,  Yuzhuo Ren ,  Atousa Torabi ,  Shubhadeep Das ,  Niranjan Avadhanam ,  Sumit Kumar Bhattacharya ,  Jason Roche

IPC: G06V40/10 ,  G06F3/01 ,  G06F16/632 ,  G06T7/73 ,  G06T15/06

Abstract: Interactions with virtual systems may be difficult when users inadvertently fail to provide sufficient information to proceed with their requests. Certain types of inputs, such as auditory inputs, may lack sufficient information to properly provide a response to the user. Additional information, such as image data, may enable user gestures or poses to supplement the auditory inputs to enable response generation without requesting additional information from users.

公开(公告)号：US12162418B2

公开(公告)日：2024-12-10

申请号：US18481603

申请日：2023-10-05

Applicant: NVIDIA Corporation

Inventor： Atousa Torabi ,  Sakthivel Sivaraman ,  Niranjan Avadhanam ,  Shagan Sah

IPC: B60R21/017 ,  B60R21/013 ,  B60W50/14 ,  B60W60/00 ,  G06N3/02 ,  B60R21/01 ,  B60W50/00

Abstract: In various examples, systems and methods are disclosed that accurately identify driver and passenger in-cabin activities that may indicate a biomechanical distraction that prevents a driver from being fully engaged in driving a vehicle. In particular, image data representative of an image of an occupant of a vehicle may be applied to one or more deep neural networks (DNNs). Using the DNNs, data indicative of key point locations corresponding to the occupant may be computed, a shape and/or a volume corresponding to the occupant may be reconstructed, a position and size of the occupant may be estimated, hand gesture activities may be classified, and/or body postures or poses may be classified. These determinations may be used to determine operations or settings for the vehicle to increase not only the safety of the occupants, but also of surrounding motorists, bicyclists, and pedestrians.