公开(公告)号：US12204969B2

公开(公告)日：2025-01-21

申请号：US17893376

申请日：2022-08-23

Applicant: WAYMO LLC

Inventor： Justin Thorsen ,  Changchang Wu ,  Alper Ayvaci ,  Tiffany Chen ,  Lo Po Tsui ,  Zhinan Xu ,  Chen Wu ,  Sean Rafferty

IPC: G06K19/067 ,  G09F3/00

Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data, for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.

公开(公告)号：US11514310B2

公开(公告)日：2022-11-29

申请号：US16231297

申请日：2018-12-21

Applicant: Waymo LLC

Inventor： Junhua Mao ,  Lo Po Tsui ,  Congcong Li ,  Edward Stephen Walker, Jr.

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.

公开(公告)号：US20220358314A1

公开(公告)日：2022-11-10

申请号：US17314925

申请日：2021-05-07

Applicant: Waymo LLC

Inventor： Yulai Shen ,  Henrik Kretzschmar ,  Jeffrey Sham ,  Jeffrey Carlson ,  Lo Po Tsui ,  Dragomir Anguelov

IPC: G06K9/00 ,  G06K9/32 ,  G06N20/00

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and editing object track labels for objects detected in video data. One of the methods includes obtaining a video segment comprising multiple image frames associated with multiple time points; obtaining object track data specifying a set of object tracks; providing, for presentation to a user, a user interface for modifying the object track data, the user interface displaying object timeline representations of the object tracks; receiving one or more user inputs that indicate one or more modifications to the object timeline representations; updating the object timeline representations displayed in the timeline display area; and updating the object track data according to the updated object timeline representations.

公开(公告)号：US20210303956A1

公开(公告)日：2021-09-30

申请号：US16827835

申请日：2020-03-24

Applicant: WAYMO LLC

Inventor： Justin Thorsen ,  Changchang Wu ,  Alper Ayvaci ,  Tiffany Chen ,  Lo Po Tsui ,  Zhinan Xu ,  Chen Wu ,  Sean Rafferty

IPC: G06K19/067 ,  G09F3/00

Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a first vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for a vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. The object is a static object may be determined. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.