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公开(公告)号：US20240251114A1
公开(公告)日：2024-07-25
申请号：US18100386
申请日：2023-01-23
Applicant: NVIDIA Corporation
IPC: H04N21/234 , H04N21/258
CPC classification number: H04N21/23418 , H04N21/25833
Abstract: Systems and methods for improved media stream processing. In at least one embodiment, a media stream is assigned to either a hardware processing engine or software processing engine based on a performance state of an application server and one or more parameters of the media stream.
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12.发明公开公开(公告)号：US20240202936A1
公开(公告)日：2024-06-20
申请号：US18542389
申请日：2023-12-15
Applicant: NVIDIA Corporation
Inventor： Joonhwa Shin , Fangyu Li , Hugo Maxence Verjus , Zheng Liu , Kaustubh Purandare
CPC classification number: G06T7/20 , G06V10/761
Abstract: A first visual appearance descriptor associated with a first object in an environment is obtained based on a first set of images of a first time period. The first object is subsequently absent from the environment in a second set of images of a second time period. A second visual appearance descriptor associated with a second object is obtained based on a third set of images, of a third time period subsequent to the second time period. A compound similarity metric between the first and second objects is obtained in view of visual appearance similarity and motion similarity metrics. The visual appearance similarity metric corresponds to a degree of similarity between the first and second visual appearance descriptors. An identifier associated with the second object is updated to correspond to an identifier associated with the first object in response to determining that the compound similarity metric meets a threshold value.
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公开(公告)号：US11995895B2
公开(公告)日：2024-05-28
申请号：US16887574
申请日：2020-05-29
Applicant: NVIDIA Corporation
Inventor： Joonhwa Shin , Zheng Liu , Kaustubh Purandare
CPC classification number: G06T7/292 , G06F17/15 , G06T1/20 , G06T11/20 , G06V10/764 , G06V10/82 , G06V20/10 , G06V20/58 , G06T2210/12
Abstract: In various examples, image areas may be extracted from a batch of one or more images and may be scaled, in batch, to one or more template sizes. Where the image areas include search regions used for localization of objects, the scaled search regions may be loaded into Graphics Processing Unit (GPU) memory and processed in parallel for localization. Similarly, where image areas are used for filter updates, the scaled image areas may be loaded into GPU memory and processed in parallel for filter updates. The image areas may be batched from any number of images and/or from any number of single- and/or multi-object trackers. Further aspects of the disclosure provide approaches for associating locations using correlation response values, for learning correlation filters in object tracking based at least on focused windowing, and for learning correlation filters in object tracking based at least on occlusion maps.
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14.发明申请公开(公告)号：US20250097471A1
公开(公告)日：2025-03-20
申请号：US18370762
申请日：2023-09-20
Applicant: NVIDIA Corporation
IPC: H04N19/65 , H04N19/172 , H04N19/46
Abstract: A processing device encodes a frame of a video. The processing device determines a reference checksum of the frame. The processing device adds the reference checksum to supplemental metadata associated with the encoded frame of the video. The processing device transmits the encoded frame and the supplemental metadata including the reference checksum to a recipient. The recipient is to use the reference checksum to verify an integrity of the frame.
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Patent Agency Ranking
15.发明申请公开(公告)号：US20250028994A1
公开(公告)日：2025-01-23
申请号：US18224362
申请日：2023-07-20
Applicant: NVIDIA Corporation
Inventor： Swapnil Jagdish Rathi , Bhushan Rupde , Kaustubh Purandare
IPC: G06N20/00
Abstract: Disclosed are apparatuses, systems, and techniques for implementing automatic runtime selection and tuning of MLM processing pipelines using stream augmentation. In one embodiment, the techniques include augmenting data stream(s) with auxiliary data to obtain an augmented data stream. The techniques further include performing an inference processing of the augmented data stream using a machine learning model (MLM) to obtain a characterization of a presence of the auxiliary data in the augmented data stream and adjusting one or more runtime settings of the MLM using the obtained characterization.
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公开(公告)号：US20220035684A1
公开(公告)日：2022-02-03
申请号：US17330710
申请日：2021-05-26
Applicant: NVIDIA Corporation
Inventor： Shaunak Gupte , Amit Kale , Bhushan Rupde , Kaustubh Purandare
Abstract: Apparatuses, systems, and techniques to balance processing load between a plurality of hardware accelerators. In at least one embodiment, operations performed on batches of frames of a video (e.g., as part of a video analytics pipeline) are distributed by a load balancer between a first hardware accelerator and a second hardware accelerator.
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公开(公告)号：US20210334629A1
公开(公告)日：2021-10-28
申请号：US17116229
申请日：2020-12-09
Applicant: NVIDIA Corporation
Inventor： Wind Yuan , Kaustubh Purandare , Bhushan Rupde , Shaunak Gupte , Farzin Aghdasi
Abstract: A multi-stage multimedia inferencing pipeline may be set up and executed using configuration data including information used to set up each stage by deploying the specified or desired models and/or other pipeline components into a repository (e.g., a shared folder in a repository). The configuration data may also include information a central inference server library uses to manage and set parameters for these components with respect to a variety of inference frameworks that may be incorporated into the pipeline. The configuration data can define a pipeline that encompasses stages for video decoding, video transform, cascade inferencing on different frameworks, metadata filtering and exchange between models and display. The entire pipeline can be efficiently hardware-accelerated using parallel processing circuits (e.g., one or more GPUs, CPUs, DPUs, or TPUs). Embodiments of the present disclosure can integrate an entire video/audio analytics pipeline into an embedded platform in real time.
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公开(公告)号：US20210117859A1
公开(公告)日：2021-04-22
申请号：US17015318
申请日：2020-09-09
Applicant: Nvidia Corporation
Inventor： Philip J. Rogers , Bhanu Pisupati , Tushar Khinvasara , Rajat Chopra , Kaustubh Purandare
Abstract: Resources, such as machine learning models, can be updated for an application without any significant downtime for that application. For an application hosted at a network edge, the application can be deployed in a container and one or more model versions stored in local storage at the edge, which can be mounted into the container as necessary. When a different model version is to be used, a configuration change or new context can be used to trigger the application to automatically change to the different model version. This updating can be performed seamlessly, without any loss of data.
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公开(公告)号：US20200380274A1
公开(公告)日：2020-12-03
申请号：US16887574
申请日：2020-05-29
Applicant: NVIDIA Corporation
Inventor： Joonhwa Shin , Zheng Liu , Kaustubh Purandare
Abstract: In various examples, image areas may be extracted from a batch of one or more images and may be scaled, in batch, to one or more template sizes. Where the image areas include search regions used for localization of objects, the scaled search regions may be loaded into Graphics Processing Unit (GPU) memory and processed in parallel for localization. Similarly, where image areas are used for filter updates, the scaled image areas may be loaded into GPU memory and processed in parallel for filter updates. The image areas may be batched from any number of images and/or from any number of single- and/or multi-object trackers. Further aspects of the disclosure provide approaches for associating locations using correlation response values, for learning correlation filters in object tracking based at least on focused windowing, and for learning correlation filters in object tracking based at least on occlusion maps.
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