Optical flow based motion detection

    公开(公告)号:US11669980B2

    公开(公告)日:2023-06-06

    申请号:US17384654

    申请日:2021-07-23

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating motion detection based on optical flow. One of the methods includes obtaining a first image of a scene in an environment taken by an agent at a first time point and a second image of the scene at a second later time point. A point cloud characterizing the scene in the environment is obtained. A predicted optical flow is determined between the first image and the second image. A respective initial flow prediction for the point that represents motion of the point between the two time points is determined. A respective ego motion flow estimate for the point that represents a motion of the point induced by ego motion of the agent is determined. A respective motion prediction that indicates whether the point was static or in motion between the two time points is determined.

    OPTICAL FLOW BASED MOTION DETECTION

    公开(公告)号:US20230033989A1

    公开(公告)日:2023-02-02

    申请号:US17384654

    申请日:2021-07-23

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating motion detection based on optical flow. One of the methods includes obtaining a first image of a scene in an environment taken by an agent at a first time point and a second image of the scene at a second later time point. A point cloud characterizing the scene in the environment is obtained. A predicted optical flow is determined between the first image and the second image. A respective initial flow prediction for the point that represents motion of the point between the two time points is determined. A respective ego motion flow estimate for the point that represents a motion of the point induced by ego motion of the agent is determined. A respective motion prediction that indicates whether the point was static or in motion between the two time points is determined.

    Identification of spurious radar detections in autonomous vehicle applications

    公开(公告)号:US12276752B2

    公开(公告)日:2025-04-15

    申请号:US17445129

    申请日:2021-08-16

    Applicant: Waymo LLC

    Abstract: The described aspects and implementations enable fast and accurate verification of radar detection of objects in autonomous vehicle (AV) applications using combined processing of radar data and camera images. In one implementation, disclosed is a method and a system to perform the method that includes obtaining a radar data characterizing intensity of radar reflections from an environment of the AV, identifying, based on the radar data, a candidate object, obtaining a camera image depicting a region where the candidate object is located, and processing the radar data and the camera image using one or more machine-learning models to obtain a classification measure representing a likelihood that the candidate object is a real object.

    Generating scene flow labels for point clouds using object labels

    公开(公告)号:US12106528B2

    公开(公告)日:2024-10-01

    申请号:US17684334

    申请日:2022-03-01

    Applicant: Waymo LLC

    CPC classification number: G06T9/002 G06F18/2148

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.

    GENERATING SCENE FLOW LABELS FOR POINT CLOUDS USING OBJECT LABELS

    公开(公告)号:US20220319054A1

    公开(公告)日:2022-10-06

    申请号:US17684334

    申请日:2022-03-01

    Applicant: Waymo LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.

    IDENTIFICATION OF SPURIOUS RADAR DETECTIONS IN AUTONOMOUS VEHICLE APPLICATIONS

    公开(公告)号:US20230046274A1

    公开(公告)日:2023-02-16

    申请号:US17445129

    申请日:2021-08-16

    Applicant: Waymo LLC

    Abstract: The described aspects and implementations enable fast and accurate verification of radar detection of objects in autonomous vehicle (AV) applications using combined processing of radar data and camera images. In one implementation, disclosed is a method and a system to perform the method that includes obtaining a radar data characterizing intensity of radar reflections from an environment of the AV, identifying, based on the radar data, a candidate object, obtaining a camera image depicting a region where the candidate object is located, and processing the radar data and the camera image using one or more machine-learning models to obtain a classification measure representing a likelihood that the candidate object is a real object.

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