公开(公告)号：US20220164595A1

公开(公告)日：2022-05-26

申请号：US17104989

申请日：2020-11-25

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

Inventor： Yao ZHOU ,  Guowei WAN ,  Shenhua HOU ,  Shiyu SONG

IPC: G06K9/62 ,  G06K9/00

Abstract: The present disclosure provides a method, an apparatus, an electronic device and a storage medium for vehicle localization, which relates to the technical fields of autonomous driving, electronic map, deep learning, image processing, and the like. In the method, a computing device obtains an image descriptor map corresponding to a captured image of an external environment of a vehicle and a predicted pose of the vehicle when the captured image is captured; obtains a set of reference descriptors and a set of spatial coordinates corresponding to a set of keypoints of a reference image of the external environment; determines a plurality of sets of image descriptors corresponding to the set of spatial coordinates when the vehicle is in a plurality of candidate poses, respectively; determines a plurality of similarities between the plurality of sets of image descriptors and the set of reference descriptors; and updates the predicted pose based on the plurality of candidate poses and the plurality of similarities. Embodiments of the present disclosure can improve localization accuracy and robustness of the vehicle visual localization algorithm.

公开(公告)号：US20220164603A1

公开(公告)日：2022-05-26

申请号：US17105027

申请日：2020-11-25

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

Inventor： Yao ZHOU ,  Guowei WAN ,  Shenhua HOU ,  Shiyu SONG

IPC: G06K9/62 ,  G06N3/08 ,  G06K9/20

Abstract: The present disclosure provides a data processing method, an apparatus, an electronic device and a medium, which relates to the technical fields of autonomous driving, electronic maps, deep learning, image processing, and the like. The method includes: a computing device inputs a reference image and a captured image into a feature extraction model; obtain, a set of reference descriptors based on the first descriptor map; determine a plurality of sets of training descriptors; obtain a predicted pose of the vehicle by inputting the plurality of training poses and a plurality of similarities into a pose prediction model; and train the feature extraction model and the pose prediction model. When applied to a vehicle localization system, the trained feature extraction model and pose prediction model according to some embodiments of the present disclosure can improve accuracy and robustness of vehicle localization, thereby boosting the performance of the vehicle localization system.

公开(公告)号：US20210209792A1

公开(公告)日：2021-07-08

申请号：US17209159

申请日：2021-03-22

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

Inventor： Yao ZHOU ,  Guowei WAN ,  Shiyu SONG

IPC: G06T7/73 ,  G06K9/46

Abstract: A positioning method includes acquiring an image of an area where a target object is located at a first time instant and multiple frames of point cloud data of an area where the target object is located at multiple time instants, wherein the multiple frames of point cloud data include first point cloud data of the area where the target object is located at the first time instant. The method also includes determining a point cloud map according to the multiple frames of point cloud data and acquiring a target feature vector according to the first point cloud data, the point cloud map and the image. The method further includes determining a positioning result of the target object according to the target feature vector.