ADAPTIVE PERCEPTUAL QUALITY BASED CAMERA TUNING USING REINFORCEMENT LEARNING

    公开(公告)号:US20240089592A1

    公开(公告)日:2024-03-14

    申请号:US18466296

    申请日:2023-09-13

    IPC分类号: H04N23/60 H04N23/61

    CPC分类号: H04N23/64 H04N23/61

    摘要: Systems and methods are provided for dynamically tuning camera parameters in a video analytics system to optimize analytics accuracy. A camera captures a current scene, and optimal camera parameter settings are learned and identified for the current scene using a Reinforcement Learning (RL) engine. The learning includes defining a state within the RL engine as a tuple of two vectors: a first representing current camera parameter values and a second representing measured values of frames of the current scene. Quality of frames is estimated using a quality estimator, and camera parameters are adjusted based on the quality estimator and the RL engine for optimization. Effectiveness of tuning is determined using perceptual Image Quality Assessment (IQA) to quantify a quality measure. Camera parameters are adaptively tuned in real-time based on learned optimal camera parameter settings, state, quality measure, and set of actions, to optimize the analytics accuracy for video analytics tasks.

    APPLICATION-CENTRIC DESIGN FOR 5G AND EDGE COMPUTING APPLICATIONS

    公开(公告)号:US20220374259A1

    公开(公告)日:2022-11-24

    申请号:US17730499

    申请日:2022-04-27

    IPC分类号: G06F9/48

    摘要: A method for specifying and executing an application including multiple microservices on 5G slices within a multi-tiered 5G infrastructure is presented. The method includes managing compute requirements and network requirements of the application simultaneously by determining end-to-end application characteristics by employing an application slice specification including an application ID component, an application name component, an application metadata component, a function dependencies component, a function instances component, and an instance connections component, specifying a function slice specification including a function network slice specification and a function compute slice specification, and employing a runtime component including a resource manager, an application slice controller, and an application slice monitor, wherein the resource manager maintains a database and manages starting, stopping, updating, and deleting application instances.

    Object recognizer emulation
    4.
    发明授权

    公开(公告)号:US11354935B2

    公开(公告)日:2022-06-07

    申请号:US16810061

    申请日:2020-03-05

    摘要: A computer-implemented method for emulating an object recognizer includes receiving testing image data, and emulating, by employing a first object recognizer, a second object recognizer. Emulating the second object recognizer includes using the first object recognizer to perform object recognition on a testing object from the testing image data to generate data, the data including a feature representation for the testing object, and classifying the testing object based on the feature representation and a machine learning model configured to predict whether the testing object would be recognized by a second object recognizer. The method further includes triggering an action to be performed based on the classification.

    FREE FLOW FEVER SCREENING
    5.
    发明申请

    公开(公告)号:US20210378520A1

    公开(公告)日:2021-12-09

    申请号:US17325613

    申请日:2021-05-20

    IPC分类号: A61B5/01 A61B5/00

    摘要: A method for free flow fever screening is presented. The method includes capturing a plurality of frames from thermal data streams and visual data streams related to a same scene to define thermal data frames and visual data frames, detecting and tracking a plurality of individuals moving in a free-flow setting within the visual data frames, and generating a tracking identification for each individual of the plurality of individuals present in a field-of-view of the one or more cameras across several frames of the plurality of frames. The method further includes fusing the thermal data frames and the visual data frames, measuring, by a fever-screener, a temperature of each individual of the plurality of individuals within and across the plurality of frames derived from the thermal data streams and the visual data streams, and generating a notification when a temperature of an individual exceeds a predetermined threshold temperature.

    OBJECT RECOGNIZER EMULATION
    6.
    发明申请

    公开(公告)号:US20200293758A1

    公开(公告)日:2020-09-17

    申请号:US16810061

    申请日:2020-03-05

    IPC分类号: G06K9/00 G06K9/62 G06N20/00

    摘要: A computer-implemented method for emulating an object recognizer includes receiving testing image data, and emulating, by employing a first object recognizer, a second object recognizer. Emulating the second object recognizer includes using the first object recognizer to perform object recognition on a testing object from the testing image data to generate data, the data including a feature representation for the testing object, and classifying the testing object based on the feature representation and a machine learning model configured to predict whether the testing object would be recognized by a second object recognizer. The method further includes triggering an action to be performed based on the classification.

    VIDEO ANALYTIC SYSTEM FOR CROWD CHARACTERIZATION

    公开(公告)号:US20210303870A1

    公开(公告)日:2021-09-30

    申请号:US17208572

    申请日:2021-03-22

    IPC分类号: G06K9/00 G06Q30/02

    摘要: A computer-implemented method for characterizing a crowd that includes recording a video stream of individuals at a location having at least one reference point for viewing; and extracting the individuals from frames of the video streams. The method may further include assigning tracking identification values to the individuals that have been extracted from the video streams; and measuring at least one type classification from the individuals having the tracking identification values. The method may further include generating a crowd designation further characterizing the individuals having the tracking identification values in the location, the crowd designation comprising at least one measurement of probability that the individuals having the tracking identification values in the location view the at least one reference point for viewing.