公开(公告)号：US20220004801A1

公开(公告)日：2022-01-06

申请号：US17480053

申请日：2021-09-20

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Zhikang ZOU ,  Xiaoqing YE ,  Hao SUN

IPC: G06K9/62 ,  G06K9/46 ,  G06T7/73 ,  G06N3/08

Abstract: The present disclosure provides an image processing method and apparatus, a training method for a neural network and apparatus, a device, and a medium. The implementation is: inputting a source domain image and a target domain image into a matching feature extraction network to extract a matching feature of the source domain image and a matching feature of the target domain image, wherein the matching feature of the source domain image and the matching feature of target domain image are mutually matching features in the source domain image and the target domain image, the source domain image is a simulated image generated through rendering based on object pose parameters, and the target domain image is a real image that is actually shot and applicable to training of object pose estimation; and providing the matching feature of the source domain image for the training of the object pose estimation.

公开(公告)号：US20210358169A1

公开(公告)日：2021-11-18

申请号：US17339177

申请日：2021-06-04

Applicant: Beijing Baidu Netcom Science and Technology Co., Ltd.

Inventor： Zhikang ZOU ,  Xiaoqing YE ,  Xiao TAN ,  Hao SUN

IPC: G06T7/80 ,  G06T7/73

Abstract: A method and an apparatus for calibrating an external parameter of a camera are provided. The method may include: acquiring a time-synchronized data set of three-dimensional point clouds and two-dimensional image of a calibration reference object, the two-dimensional image being acquired by a camera with a to-be-calibrated external parameter; establishing a transformation relationship between a point cloud coordinate system and an image coordinate system, the transformation relationship including a transformation parameter; back-projecting the data set of the three-dimensional point clouds onto a plane where the two-dimensional image is located through the transformation relationship to obtain a set of projection points of the three-dimensional point clouds; adjusting the transformation parameter to map the set of the projection points onto the two-dimensional image; and obtaining an external parameter of the camera based on the adjusted transformation parameter and the data set of the three-dimensional point clouds.