公开(公告)号：US20200237266A1

公开(公告)日：2020-07-30

申请号：US16846890

申请日：2020-04-13

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yu QIAO ,  Wenbin DU ,  Yali WANG ,  Lihui JIANG ,  Jianzhuang LIU

IPC: A61B5/11 ,  A61B5/00 ,  G06K9/48 ,  G06K9/00 ,  G06N3/08

Abstract: Action recognition methods are disclosed. An embodiment of the methods includes: identifying a video that comprises images of a human body to be processed; identifying at least one image to be processed, wherein the at least one image is at least one of an optical flow image generated based on a plurality of frames of images in the video, or a composite image of one or more frames of images in the video; performing convolution on the at least one image to obtain a plurality of eigenvectors, wherein the plurality of eigenvectors indicate a plurality of features of different locations in the at least one image; determining a weight coefficient set of each of a plurality of human joints of the human body based on the plurality of eigenvectors, wherein the weight coefficient set comprises a weight coefficient of each of the plurality of eigenvectors for the human joint; weighting the plurality of eigenvectors based on the weight coefficient set to obtain an action feature of each of the plurality of human joints; determining an action feature of the human body based on the action feature of each of the human joints; and determining an action type of the human body based on the action feature of the human body.

公开(公告)号：US20220148328A1

公开(公告)日：2022-05-12

申请号：US17586136

申请日：2022-01-27

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Qixiang YE ,  Tianliang ZHANG ,  Jianzhuang LIU ,  Xiaopeng ZHANG ,  QI TIAN ,  Lihui JIANG

IPC: G06V40/10 ,  G06V10/25 ,  G06V10/80 ,  G06V10/77 ,  G06V10/44 ,  G06V10/82 ,  G06V20/58 ,  G06V20/52

Abstract: This application relates to the field of artificial intelligence, and specifically, to the field of computer vision. The method includes: performing feature extraction on an image to obtain a basic feature map of the image; determining a proposal of a region possibly including a pedestrian in the image; processing the basic feature map of the image to obtain an object visibility map in which a response to a pedestrian visible part is greater than a response to a pedestrian blocked part and a background part; performing weighted summation processing on the object visibility map and the basic feature map to obtain an enhanced feature map of the image; and determining, based on the proposal of the image and the enhanced feature map of the image, a bounding box including a pedestrian in the image and a confidence level of the bounding box including the pedestrian in the image.