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    EFFICIENT THREE-DIMENSIONAL OBJECT DETECTION FROM POINT CLOUDS
    2.
    发明申请
    EFFICIENT THREE-DIMENSIONAL OBJECT DETECTION FROM POINT CLOUDS 有权

    公开(公告)号：US20220156483A1

    公开(公告)日：2022-05-19

    申请号：US17527653

    申请日：2021-11-16

    Applicant: Waymo LLC

    Inventor： Pei Sun ,  Weiyue Wang ,  Yuning Chai ,  Xiao Zhang ,  Dragomir Anguelov

    IPC: G06K9/00 ,  G06T7/194

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing object detection. The system obtains a respective range image corresponding to each point cloud in a set of point clouds captured by one or more sensors. The system processes each range image using a segmentation neural network to generate range image features and a segmentation output. The system generates a feature representation of the set of point clouds from only the feature representations of the foreground points. The system processes the feature representation of the set of point clouds using a prediction neural network to generate a prediction characterizing the set of point clouds.

    Controlling vehicles through multi-lane turns
    4.
    发明授权
    Controlling vehicles through multi-lane turns 有权

    公开(公告)号：US11054834B2

    公开(公告)日：2021-07-06

    申请号：US16165114

    申请日：2018-10-19

    Applicant: Waymo LLC

    Inventor： Jared Stephen Russell ,  Jens-Steffen Ralf Gutmann ,  Pei Sun

    IPC: G05D1/02 ,  G05D1/00 ,  B60W30/18

    Abstract: The technology relates controlling an autonomous vehicle through a multi-lane turn. In one example, data corresponding to a position of the autonomous vehicle in a lane of the multi-lane turn, a trajectory of the autonomous vehicle, and data corresponding to positions of objects in a vicinity of the autonomous vehicle may be received. A determination of whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane may be made based on a position of the autonomous vehicle in the lane relative to the positions of the objects. The trajectory of the autonomous vehicle through the lane may be adjusted based on whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane. The autonomous vehicle may be controlled based on the adjusted trajectory.

    Efficient three-dimensional object detection from point clouds
    8.
    发明授权
    Efficient three-dimensional object detection from point clouds 有权

    公开(公告)号：US12125298B2

    公开(公告)日：2024-10-22

    申请号：US17527653

    申请日：2021-11-16

    Applicant: Waymo LLC

    Inventor： Pei Sun ,  Weiyue Wang ,  Yuning Chai ,  Xiao Zhang ,  Dragomir Anguelov

    IPC: G06V20/64 ,  G06T7/194

    CPC classification number: G06V20/64 ,  G06T7/194 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20084

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing object detection. The system obtains a respective range image corresponding to each point cloud in a set of point clouds captured by one or more sensors. The system processes each range image using a segmentation neural network to generate range image features and a segmentation output. The system generates a feature representation of the set of point clouds from only the feature representations of the foreground points. The system processes the feature representation of the set of point clouds using a prediction neural network to generate a prediction characterizing the set of point clouds.

    Object-centric three-dimensional auto labeling of point cloud data
    9.
    发明授权
    Object-centric three-dimensional auto labeling of point cloud data 有权

    公开(公告)号：US12073575B2

    公开(公告)日：2024-08-27

    申请号：US17407795

    申请日：2021-08-20

    Applicant: Waymo LLC

    Inventor： Ruizhongtai Qi ,  Yin Zhou ,  Dragomir Anguelov ,  Pei Sun

    IPC: G06T7/521 ,  G06T7/20

    CPC classification number: G06T7/521 ,  G06T7/20 ,  G06T2207/10028 ,  G06T2207/20084

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing three-dimensional auto-labeling on sensor data. The system obtains a sensor data segment that includes a temporal sequence of three-dimensional point clouds generated from sensor readings of an environment by one or more sensors. The system identifies, from the sensor data segment, (i) a plurality of object tracks that each corresponds to a different object in the environment and (ii) for each object track, respective initial three-dimensional regions in each of one or more of the point clouds in which the corresponding object appears. The system generates, for each object track, extracted object track data that includes at least the points in the respective initial three-dimensional regions for the object track. The system further generates, for each object track and from the extracted object track data for the object track, an auto labeling output that defines respective refined three-dimensional regions in each of the one or more point clouds.

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