公开(公告)号：US11758285B2

公开(公告)日：2023-09-12

申请号：US17330133

申请日：2021-05-25

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Daxin Luo ,  Fenglong Song ,  Songcen Xu ,  Yi Liu ,  Youliang Yan ,  Jianzhuang Liu ,  Li Qian

IPC: G06T7/246 ,  H04N23/80 ,  G06T7/00 ,  H04N23/63

CPC classification number: H04N23/80 ,  G06T7/0002 ,  G06T7/246 ,  H04N23/63 ,  G06T2207/10016 ,  G06T2207/30168

Abstract: In a method for selecting pictures from a sequence of pictures of an object in motion, a computerized user device determines, for each picture in the sequence of pictures, a value of a motion feature of the object. Based on analyzing the values of the motion feature of the pictures in the sequence, the device identifies a first subset of pictures from the pictures in the sequence. The device then selects, based on a second selection criterion, a second subset of pictures from the first subset of pictures. The pictures in the second subset are displayed to a user for further selection.

公开(公告)号：US11478169B2

公开(公告)日：2022-10-25

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 ,  G06N3/08 ,  G06V10/46 ,  G06V40/10

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：US20210258506A1

公开(公告)日：2021-08-19

申请号：US17308535

申请日：2021-05-05

Applicant: Huawei Technologies Co., Ltd.

Inventor： Zhihao Li ,  Xiaofei Wu ,  Songcen Xu ,  Jianzhuang Liu ,  Youliang Yan

IPC: H04N5/232 ,  G06T7/11

Abstract: An image processing method includes detecting human skeleton key points of a character in an image, and for the to-be-processed image, generating a cropping region based on the human skeleton key points and a preset rule, and using the to-be-processed image selected by using the cropping region as an output object. The human skeleton key points and the preset rule are set based on photographing experience.

公开(公告)号：US20210012164A1

公开(公告)日：2021-01-14

申请号：US17034654

申请日：2020-09-28

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yu Qiao ,  Lei Zhou ,  Yali Wang ,  Lihui Jiang ,  Jianzhuang Liu

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/46

Abstract: An action recognition method and apparatus related to artificial intelligence and include extracting a spatial feature of a to-be-processed picture, determining a virtual optical flow feature of the to-be-processed picture based on the spatial feature and X spatial features and X optical flow features in a preset feature library, where the X spatial features and the X optical flow features include a one-to-one correspondence, determining a first type of confidence of the to-be-processed picture in different action categories based on similarities between the virtual optical flow feature and Y optical flow features, where each of the Y optical flow features in the preset feature library corresponds to one action category, X and Y are both integers greater than 1, and determining an action category of the to-be-processed picture based on the first type of confidence.

公开(公告)号：US20170039761A1

公开(公告)日：2017-02-09

申请号：US15296138

申请日：2016-10-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Wei Zhang ,  Chunjing Xu ,  Jianzhuang Liu

IPC: G06T17/10 ,  G06T7/00

CPC classification number: G06T17/10 ,  G06T7/12 ,  G06T7/13 ,  G06T7/149 ,  G06T17/00 ,  G06T2207/10004 ,  G06T2207/20096 ,  G06T2207/20124 ,  G06T2207/30201

Abstract: An image processing method and apparatus are disclosed. The method includes obtaining a two-dimensional target face image, receiving an identification curve marked by a user in the target face image, locating a facial contour curve of a face from the target face image according to the identification curve and by using an image segmentation technology, determining a three-dimensional posture and a feature point position of the face in the target face image, and constructing a three-dimensional shape of the face in the target face image according to the facial contour curve, the three-dimensional posture, and the feature point position of the face in the target face image by using a preset empirical model of a three-dimensional face shape and a target function matching the empirical model of the three-dimensional face shape. Using the method and apparatus, the complexity of three-dimensional face shape construction can be reduced.

Abstract translation: 公开了一种图像处理方法和装置。 该方法包括：获取二维目标人脸图像，接收由目标脸部图像中的用户标记的识别曲线，根据识别曲线从目标人脸图像定位面部的面部轮廓曲线，并通过使用图像分割 确定目标面部图像中的面部的三维姿态和特征点位置，根据面部轮廓曲线，三维姿势，面部轮廓曲线构成面部的三维形状， 以及通过使用三维脸部形状的预设经验模型和与三维脸部形状的经验模型相匹配的目标函数，在目标脸部图像中的脸部的特征点位置。 使用该方法和装置，可以减少三维面形结构的复杂性。