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1.
公开(公告)号:US12169942B2
公开(公告)日:2024-12-17
申请号:US17324174
申请日:2021-05-19
Inventor: Minyue Jiang , Xipeng Yang , Xiao Tan , Hao Sun
Abstract: A method for training an image depth estimation model. A sample environmental image, sample environmental point cloud data and sample edge information of the sample environmental image are input into a to-be-trained model; initial depth information of each of pixel points in the sample environmental image and a feature relationship between each of the pixel points and a corresponding neighboring pixel point of each of the pixel points are determined through the to-be-trained model, the initial depth information of each of the pixel points is optimized according to the feature relationship to obtain optimized depth information of each of the pixel points, and a parameter of the to-be-trained model is adjusted according to the optimized depth information to obtain the image depth estimation model.
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2.
公开(公告)号:US20230009547A1
公开(公告)日:2023-01-12
申请号:US17933271
申请日:2022-09-19
Inventor: Xipeng Yang , Xiao Tan , Hao Sun , Errui Ding
IPC: G06V10/77 , G06V10/80 , G06V10/764 , G06V10/26
Abstract: A method for detecting an object based on a video includes: obtaining a plurality of image frames of a video to be detected; obtaining initial feature maps by extracting features of the plurality of image frames; for each two adjacent image frames of the plurality of image frames, obtaining a target feature map of a latter image frame of the two adjacent image frames by performing feature fusing on the sub-feature maps of the first target dimensions included in the initial feature map of a former image frame of the two adjacent image frames and the sub-feature maps of the second target dimensions included in the initial feature map of the latter image frame; and performing object detection on the respective target feature map of each image frame.
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公开(公告)号:US11288887B2
公开(公告)日:2022-03-29
申请号:US16869411
申请日:2020-05-07
Inventor: Xipeng Yang , Xiao Tan , Hao Sun , Shilei Wen , Errui Ding
Abstract: Embodiments of the present disclosure provide an object tracking method and an apparatus. The method includes: obtaining multiple frames of first images shot by a first camera apparatus and a first shooting moment of each frame of the first images, where the first images include a first object; obtaining multiple frames of second images shot by a second camera apparatus and a second shooting moment of each frame of the second images, where the second images include a second object; obtaining a distance between the first camera apparatus and the second camera apparatus; and judging whether the first object and the second object are the same object according to the multiple frames of the first images, the first shooting moment of each frame of the first images, the multiple frames of the second images, the second shooting moment of each frame of the second images and the distance.
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