公开(公告)号：US11010626B2

公开(公告)日：2021-05-18

申请号：US16196193

申请日：2018-11-20

Applicant: Aptiv Technologies Limited

Inventor： Alexander Barth ,  Patrick Weyers

IPC: G06K9/00 ,  G06K9/62 ,  G06K9/46 ,  G06N3/08

Abstract: A system for generating a confidence value for at least one state in the interior of a vehicle, comprising an imaging unit configured to capture at least one image of the interior of the vehicle, and a processing unit comprising a convolutional neural network, wherein the processing unit is configured to receive the at least one image from the imaging unit and to input the at least one image into the convolution-al neural network, wherein the convolutional neural network is configured to generate a respective likelihood value for each of a plurality of states in the interior of the vehicle with the likelihood value for a respective state indicating the likelihood that the respective state is present in the interior of the vehicle, and wherein the processing unit is further configured to generate a confidence value for at least one of the plurality of states in the interior of the vehicle from the likelihood values generated by the convolutional neural network.

公开(公告)号：US20190171892A1

公开(公告)日：2019-06-06

申请号：US16196193

申请日：2018-11-20

Applicant: Aptiv Technologies Limited

Inventor： Alexander Barth ,  Patrick Weyers

IPC: G06K9/00 ,  G06N3/08 ,  G06K9/62

Abstract: A system for generating a confidence value for at least one state in the interior of a vehicle, comprising an imaging unit configured to capture at least one image of the interior of the vehicle, and a processing unit comprising a convolutional neural network, wherein the processing unit is configured to receive the at least one image from the imaging unit and to input the at least one image into the convolution-al neural network, wherein the convolutional neural network is configured to generate a respective likelihood value for each of a plurality of states in the interior of the vehicle with the likelihood value for a respective state indicating the likelihood that the respective state is present in the interior of the vehicle, and wherein the processing unit is further configured to generate a confidence value for at least one of the plurality of states in the interior of the vehicle from the likelihood values generated by the convolutional neural network.

公开(公告)号：US11308722B2

公开(公告)日：2022-04-19

申请号：US17006652

申请日：2020-08-28

Applicant: Aptiv Technologies Limited

Inventor： Patrick Weyers ,  Alexander Barth ,  David Schiebener

IPC: G06K9/00 ,  G06K9/62 ,  B60W40/09 ,  G06N3/02 ,  G06V20/59

Abstract: A computer implemented method for determining an activity of an occupant of a vehicle comprises the following steps carried out by computer hardware components: capturing sensor data of the occupant using at least one sensor; determining respective two-dimensional or three-dimensional coordinates for a plurality of pre-determined portions of the body of the occupant based on the sensor data; determining at least one portion of the sensor data showing a pre-determined body part of the occupant based on the sensor data and the two-dimensional or three-dimensional coordinates; and determining the activity of the occupant based on the two-dimensional or three-dimensional coordinates and the at least one portion of the sensor data.

公开(公告)号：US20210081689A1

公开(公告)日：2021-03-18

申请号：US17006652

申请日：2020-08-28

Applicant: Aptiv Technologies Limited

Inventor： Patrick Weyers ,  Alexander Barth ,  David Schiebener

IPC: G06K9/00 ,  B60W40/09 ,  G06K9/62 ,  G06N3/02

Abstract: A computer implemented method for determining an activity of an occupant of a vehicle comprises the following steps carried out by computer hardware components: capturing sensor data of the occupant using at least one sensor; determining respective two-dimensional or three-dimensional coordinates for a plurality of pre-determined portions of the body of the occupant based on the sensor data; determining at least one portion of the sensor data showing a pre-determined body part of the occupant based on the sensor data and the two-dimensional or three-dimensional coordinates; and determining the activity of the occupant based on the two-dimensional or three-dimensional coordinates and the at least one portion of the sensor data.