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    TECHNIQUES TO SET FOCUS IN CAMERA IN A MIXED-REALITY ENVIRONMENT WITH HAND GESTURE INTERACTION
    2.
    发明申请
    TECHNIQUES TO SET FOCUS IN CAMERA IN A MIXED-REALITY ENVIRONMENT WITH HAND GESTURE INTERACTION 有权

    公开(公告)号：US20220141379A1

    公开(公告)日：2022-05-05

    申请号：US17573613

    申请日：2022-01-11

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Maria Cheng LEI ,  Vishal JAIN ,  Vikramaditya DANGI

    IPC: H04N5/232 ,  G02B7/28 ,  G02B27/01 ,  G06F3/01 ,  G06F3/04845 ,  G06T11/60

    Abstract: An adjustable-focus PV (picture/video) camera in a mixed-reality head-mounted display (HMD) device operates with an auto-focus subsystem that is configured to be triggered based on location and motion of a user's hands to reduce the occurrence of auto-focus hunting during camera operations. The HMD device is equipped with a depth sensor that is configured to capture depth data from the surrounding physical environment to detect and track the user's hand location, movements, and gestures in three-dimensions. The hand tracking data from the depth sensor may be assessed to determine hand characteristics—such as which of the user's hands or part of a hand is detected, its size, motion, speed, etc.—within a particular region of interest (ROI) in the field of view of the PV camera. The auto-focus subsystem uses the assessed hand characteristics as an input to control auto-focus of the PV camera to reduce auto-focus hunting occurrences.

    DYNAMIC POWER CAPPING OF COMPUTING SYSTEMS AND SUBSYSTEMS CONTAINED THEREIN
    3.
    发明申请
    DYNAMIC POWER CAPPING OF COMPUTING SYSTEMS AND SUBSYSTEMS CONTAINED THEREIN 有权

    公开(公告)号：US20210405728A1

    公开(公告)日：2021-12-30

    申请号：US16914080

    申请日：2020-06-26

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Vishal JAIN ,  Teague Curtiss MAPES ,  Neeraj LADKANI ,  Sunny GAUTAM

    IPC: G06F1/3228 ,  G06F1/329 ,  G06F1/3296 ,  H05K7/14

    Abstract: One aspect of the present disclosure involves dynamically performing power capping with respect to a group of computing systems. Different priority levels can be assigned to at least some of the individual computing systems within the group of computing systems. Individual power limits can be set for the plurality of individual computing systems based at least in part on the different priority levels and utilization levels of the plurality of individual computing systems. Another aspect of the present disclosure involves dynamically performing power capping with respect to various subsystems of a computing system. Different priority levels can be assigned to at least some of the plurality of individual subsystems within the computing system. Individual power limits can be set for the plurality of individual subsystems based at least in part on the different priority levels and current power consumption of the plurality of individual subsystems.

    DYNAMIC CONTROL OF CAMERA RESOURCES IN A DEVICE WITH MULTIPLE DISPLAYS
    4.
    发明申请
    DYNAMIC CONTROL OF CAMERA RESOURCES IN A DEVICE WITH MULTIPLE DISPLAYS 审中-公开

    公开(公告)号：US20190007619A1

    公开(公告)日：2019-01-03

    申请号：US15639584

    申请日：2017-06-30

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： Maria Cheng LEI ,  Vishal JAIN ,  Tomi SOKEILA ,  Raymond XUE

    IPC: H04N5/232 ,  H04N5/247

    Abstract: Methods and devices for dynamically controlling mirroring of a preview image may include receiving physical location information of a selected camera resource on the computer device, wherein the physical location information corresponds to a static orientation of the camera resource. The methods and devices may include determining a dynamic orientation of the selected camera resource based on sensor information for the selected camera resource and determining a camera role of the selected camera resource based on the dynamic orientation and the static orientation of the selected camera, wherein the camera role comprises a front facing camera role or a rear facing camera role. The methods and devices may include displaying a mirrored preview image when the camera role of the selected camera resource is the front facing camera role and displaying a non-mirrored preview image when the camera role of the selected camera resource is the rear facing camera role.

    RETRIEVING DIAGNOSTIC INFORMATION FROM A PCI EXPRESS ENDPOINT
    6.
    发明公开
    RETRIEVING DIAGNOSTIC INFORMATION FROM A PCI EXPRESS ENDPOINT 审中-公开

    公开(公告)号：US20230195552A1

    公开(公告)日：2023-06-22

    申请号：US17926078

    申请日：2021-05-18

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Vishal JAIN ,  Teague Curtiss MAPES ,  Jonathan Kent ROSS

    IPC: G06F11/07 ,  G06F13/42

    CPC classification number: G06F11/0772 ,  G06F11/0745 ,  G06F13/4221 ,  G06F2213/0026

    Abstract: The present disclosure relates to systems, methods, and computer-readable media for facilitating efficient retrieval of diagnostic information from a computing endpoint that experiences a failure condition. For example, systems described herein may detect or otherwise identify a failure condition associating with the computing endpoint operating in an erroneous or unpredictable matter. Systems described herein may involve carving out a portion of memory on the computing endpoint that is accessible to a host system (e.g., a CPU). Systems described herein may further provide a discoverable resource that enables a host system to identify and collect the diagnostic data in response to identifying a failure condition in an efficient manner and without requiring that the computing endpoint be capable of responding to data requests.

    REINFORCEMENT LEARNING SIMULATION OF SUPPLY CHAIN GRAPH
    7.
    发明申请
    REINFORCEMENT LEARNING SIMULATION OF SUPPLY CHAIN GRAPH 有权

    公开(公告)号：US20230129665A1

    公开(公告)日：2023-04-27

    申请号：US17457874

    申请日：2021-12-06

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Peeyush KUMAR ,  Hui Qing LI ,  Vaishnavi NATTAR RANGANATHAN ,  Lillian Jane RATLIFF ,  Ranveer CHANDRA ,  Vishal JAIN ,  Michael McNab BASSANI ,  Jeremy Randall REYNOLDS

    IPC: G06K9/62 ,  G06Q10/08

    Abstract: A computing system including a processor configured to receive training data including, for each of a plurality of training timesteps, training forecast states associated with respective training-phase agents included in a training supply chain graph. The processor may train a reinforcement learning simulation of the training supply chain graph using the training data via policy gradient reinforcement learning. At each training timestep, the training forecast states may be shared between simulations of the training-phase agents during training. The processor may receive runtime forecast states associated with respective runtime agents included in a runtime supply chain graph. For a runtime agent, at the trained reinforcement learning simulation, the processor may generate a respective runtime action output associated with a corresponding runtime forecast state of the runtime agent based at least in part on the runtime forecast states. The processor may output the runtime action output.

    TRACEABILITY SYSTEM FOR BULK COMMODITY SUPPLY CHAIN
    8.
    发明公开
    TRACEABILITY SYSTEM FOR BULK COMMODITY SUPPLY CHAIN 审中-公开

    公开(公告)号：US20230222433A1

    公开(公告)日：2023-07-13

    申请号：US17647924

    申请日：2022-01-13

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Vaishnavi NATTAR RANGANATHAN ,  Upinder KAUR ,  Peeyush KUMAR ,  Ranveer CHANDRA ,  Michael McNab BASSANI ,  Vishal JAIN

    IPC: G06Q10/08 ,  G06Q30/00

    CPC classification number: G06Q10/0833 ,  G06Q30/018

    Abstract: A traceability system for a bulk commodity supply chain is provided. The system includes a tracking device, a location determination subsystem, and at least one computing device having at least one processor. The location determination subsystem is configured to determine positional information of the tracking device while placed in a bulk commodity traveling along the bulk commodity supply chain. The processor receives the positional information from the location subsystem, extracts positional values from the positional information, and processes the positional values to identify motion primitives. A modeling tool is applied to the identified motion primitives to produce a positional path of the tracking device, which is output, for example, via a user interface. The positional path represents travel of the bulk commodity along the supply chain.

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