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公开(公告)号：US11871011B2
公开(公告)日：2024-01-09
申请号：US17556819
申请日：2021-12-20
Applicant: NVIDIA Corporation
Inventor： Sarvesh Satavalekar , Gordon Grigor , Vinayak Pore , Gajanan Bhat , Mohan Nimaje , Soumen Kumar Dey , Sameer Anand Gumaste
IPC: H04N19/182 , G06T7/11 , G06N3/02 , H04N19/33 , H04N19/186 , H04N1/64 , H04N9/67 , H04N1/413
CPC classification number: H04N19/182 , G06N3/02 , G06T7/11 , H04N1/413 , H04N1/64 , H04N9/67 , H04N19/186 , H04N19/33
Abstract: Systems and methods for efficient lossless compression of captured raw image information are presented. A method can comprise: receiving raw image data from an image capture device, segregating the pixel data into a base layer portion and an enhanced layer portion, reconfiguring the base layer portion expressed in the first color space values from a raw capture format into a pseudo second color space compression mechanism compatible format, and compressing the reconfigured base layer portion of first color space values. The raw image data can include pixel data are expressed in first color space values. The segregation can be based upon various factors, including a compression benefits analysis of a boundary location between the base layer portion and enhanced layer portion. The reconfiguring the base layer portion can include separating the base layer portion based upon multiple components within the raw data; and forming base layer video frames from the multiple components.
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公开(公告)号：US20190266418A1
公开(公告)日：2019-08-29
申请号：US16286329
申请日：2019-02-26
Applicant: NVIDIA Corporation
Inventor： Yifang Xu , Xin Liu , Chia-Chih Chen , Carolina Parada , Davide Onofrio , Minwoo Park , Mehdi Sajjadi Mohammadabadi , Vijay Chintalapudi , Ozan Tonkal , John Zedlewski , Pekka Janis , Jan Nikolaus Fritsch , Gordon Grigor , Zuoguan Wang , I-Kuei Chen , Miguel Sainz
Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.
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公开(公告)号：US20190082185A1
公开(公告)日：2019-03-14
申请号：US16048120
申请日：2018-07-27
Applicant: NVIDIA Corporation
Inventor： Sarvesh SATAVALEKAR , Gordon Grigor , Vinayak Pore , Gajanan Bhat , Mohan Nimaje , Soumen Dey , Sameer Gumaste
IPC: H04N19/182 , G06T7/11 , H04N19/186 , H04N19/33 , G06N3/02
Abstract: Systems and methods for efficient lossless compression of captured raw image information are presented. A method can comprise: receiving raw image data from an image capture device, segregating the pixel data into a base layer portion and an enhanced layer portion, reconfiguring the base layer portion expressed in the first color space values from a raw capture format into a pseudo second color space compression mechanism compatible format, and compressing the reconfigured base layer portion of first color space values. The raw image data can include pixel data are expressed in first color space values. The segregation can be based upon various factors, including a compression benefits analysis of a boundary location between the base layer portion and enhanced layer portion. The reconfiguring the base layer portion can include separating the base layer portion based upon multiple components within the raw data; and forming base layer video frames from the multiple components.
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公开(公告)号：US20230267701A1
公开(公告)日：2023-08-24
申请号：US18309882
申请日：2023-05-01
Applicant: NVIDIA Corporation
Inventor： Yifang Xu , Xin Liu , Chia-Chin Chen , Carolina Parada , Davide Onofrio , Minwoo Park , Mehdi Sajjadi Mohammadabadi , Vijay Chintalapudi , Ozan Tonkal , John Zedlewski , Pekka Janis , Jan Nikolaus Fritsch , Gordon Grigor , Zuoguan Wang , I-Kuei Chen , Miguel Sainz
IPC: G06V10/44 , G06T7/10 , G05D1/00 , G06N3/084 , G05D1/02 , G06V20/56 , G06V10/46 , G06V20/40 , G06F18/2413 , G06V10/764 , G06V10/82
CPC classification number: G06V10/44 , G06T7/10 , G05D1/0088 , G06N3/084 , G05D1/0221 , G06V20/588 , G06V10/46 , G06V10/457 , G06V20/41 , G06F18/24143 , G06V10/764 , G06V10/82 , G06V10/471
Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.
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公开(公告)号：US11474519B2
公开(公告)日：2022-10-18
申请号：US16286330
申请日：2019-02-26
Applicant: NVIDIA Corporation
Inventor： Gary Hicok , Michael Cox , Miguel Sainz , Martin Hempel , Ratin Kumar , Timo Roman , Gordon Grigor , David Nister , Justin Ebert , Chin Shih , Tony Tam , Ruchi Bhargava
Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.
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Patent Agency Ranking
公开(公告)号：US11212539B2
公开(公告)日：2021-12-28
申请号：US16048120
申请日：2018-07-27
Applicant: NVIDIA Corporation
Inventor： Sarvesh Satavalekar , Gordon Grigor , Vinayak Pore , Gajanan Bhat , Mohan Nimaje , Soumen Dey , Sameer Gumaste
IPC: H04N19/182 , G06T7/11 , G06N3/02 , H04N19/33 , H04N19/186 , H04N1/64 , H04N9/67 , H04N1/413
Abstract: Systems and methods for efficient lossless compression of captured raw image information are presented. A method can comprise: receiving raw image data from an image capture device, segregating the pixel data into a base layer portion and an enhanced layer portion, reconfiguring the base layer portion expressed in the first color space values from a raw capture format into a pseudo second color space compression mechanism compatible format, and compressing the reconfigured base layer portion of first color space values. The raw image data can include pixel data are expressed in first color space values. The segregation can be based upon various factors, including a compression benefits analysis of a boundary location between the base layer portion and enhanced layer portion. The reconfiguring the base layer portion can include separating the base layer portion based upon multiple components within the raw data; and forming base layer video frames from the multiple components.
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公开(公告)号：US20250117251A1
公开(公告)日：2025-04-10
申请号：US18483404
申请日：2023-10-09
Applicant: NVIDIA Corporation
Inventor： Eric COLTER , Arun SHAMANNA LAKSHMI , Gordon Grigor
IPC: G06F9/48
Abstract: Embodiments of the present disclosure relate to a system and method used to schedule and initiate execution of one or more tasks. The system may include processing units that may perform operations that may include obtaining execution information that may correspond to a first task and a second task. In some embodiments, the first task may include first operations and where the second task may include second operations. In some embodiments, the operations may further include determining a time to initialize execution of the first task and the second task based at least on the execution information. In some embodiments, execution of the first task may be executed on a first computing system and the second task may be executed on a second computing system where the execution of the first operations and the second operations is interdependent.
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公开(公告)号：US12266148B2
公开(公告)日：2025-04-01
申请号：US18309882
申请日：2023-05-01
Applicant: NVIDIA Corporation
Inventor： Yifang Xu , Xin Liu , Chia-Chih Chen , Carolina Parada , Davide Onofrio , Minwoo Park , Mehdi Sajjadi Mohammadabadi , Vijay Chintalapudi , Ozan Tonkal , John Zedlewski , Pekka Janis , Jan Nikolaus Fritsch , Gordon Grigor , Zuoguan Wang , I-Kuei Chen , Miguel Sainz
IPC: G06V10/44 , G05D1/00 , G06F18/2413 , G06N3/084 , G06T7/10 , G06V10/46 , G06V10/764 , G06V10/82 , G06V20/40 , G06V20/56
Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.
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公开(公告)号：US20240427372A1
公开(公告)日：2024-12-26
申请号：US18338027
申请日：2023-06-20
Applicant: NVIDIA Corporation
Inventor： Sean Gillen , Blake McHale , Marc R. Delvaux , Sheng-Lin Lo , Gordon Grigor
IPC: G06F1/12
Abstract: In various examples, sets of correlated timestamps are sampled from clock sources. The sets of correlated timestamps are used to compute translation data, such as offsets and/or rates of change of the clock sources. The offsets and/or rates of change may be used to translate a timestamp to a reference time domain. The sampled clock sources may be frequency locked and the translation may be performed without using the rates of change. For example, a running average of the offsets may be used to perform the translation. The translated timestamps and corresponding sensor measurements may be provided to one or more applications for use in performing one or more operations for a machine, such as perception and/or control operations.
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公开(公告)号：US20250139934A1
公开(公告)日：2025-05-01
申请号：US19005672
申请日：2024-12-30
Applicant: NVIDIA Corporation
Inventor： Yifang Xu , Xin Liu , Chia-Chih Chen , Carolina Parada , Davide Onofrio , Minwoo Park , Mehdi Sajjadi Mohammadabadi , Vijay Chintalapudi , Ozan Tonkal , John Zedlewski , Pekka Janis , Jan Nikolaus Fritsch , Gordon Grigor , Zuoguan Wang , I-Kuei Chen , Miguel Sainz
IPC: G06V10/44 , G06F18/2413 , G06N3/084 , G06T7/10 , G06V10/46 , G06V10/764 , G06V10/82 , G06V20/40 , G06V20/56
Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.
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