Huawei Technologies Co., Limited

Future Wei Technologies, Inc.

Jiali Fu

Haitao Yang

Jianle Chen

Huimin Zhang

Huanbang Chen

Kangmin Huang

Qingpeng Xie

Shan Liu

Xueyan Huang

Maosheng Huang

Tizheng Wang

Lina Tao

Duan Li

Hongkai Zhou

Huali Wang

Yin Zhao

Jiantong Zhou

Li Qian

Shan Gao

Peiyun Di

Mingjie Dong

Shanfu Li

Roman Igorevich Chernyak

Mathias Wien

Victor Alexeevich Stepin

He Wei

Fabian Jaeger

Sergey Yurievich Ikonin

Sixin Lin

Xiang Ma

Mingyuan Yang

Heng Liao

Weiwei Xu

Zhuoyi Lv

Ting Fu

Yi Song

Wenhua Sun

Igor Igorevich Pasechnik

Jose Alvarez

Jingjing Dai

Zilian Qu

Igor Pasechnik

Roman Chernyak

The present disclosure discloses a preview-image display while a terminal device photographs a picture. The method comprises: obtaining, by a terminal device, a first preview image and a second preview image, wherein the first preview image is based on a current picture in a first mode and the second preview image is based on the current picture in a second mode; and displaying, by the terminal device, a first part of the first preview image and a second part of the second preview image in a preview area, wherein the first part of the first preview image and the second part of the second preview image constitute a third preview image based on the current picture.

Preview-image display method and terminal device

A motion vector prediction method includes parsing a bitstream to obtain an index value of a candidate motion vector list and constructing the candidate motion vector list that includes. candidate motion vectors of K control points of a current block. The candidate motion vectors of K control points are obtained based on a 2N-parameter affine transform model used for a neighboring block of the current block, where N and K are integers greater than or equal to 2 and less than or equal to 4 with N not being equal to K. The method further includes determining, in the candidate motion vector list, target candidate motion vectors of the K control points based on the index value and obtaining a predicted motion vector of each subblock of the current block based on the target candidate motion vectors of the K control points.

Motion vector prediction method and related apparatus

Technologies for inter prediction for a block in a video are provided. In one example, a method includes: parsing a bitstream to obtain a syntax element, where the syntax element includes at least an index of optimal candidate motion information of a current block; determining, based on the syntax element, to construct a first list or a second list for the current block, where the first list is a block-based candidate motion information list, and the second list is a subblock-based candidate motion information list; determining optimal motion information from the first list or the second list based on the index; and predicting the current block based on the optimal motion information. In this method, the block-based candidate motion information list and the subblock-based candidate motion information list are distinguished from each other. This effectively reduces transmission costs of the optimal candidate motion information.

Motion vector prediction for video coding

Video image encoding method and related computer-readable medium and apparatus

Embodiments of the present invention provide a human-machine interaction method, including: detecting and collecting, by a robot, sensing information of a companion object of a target object and emotion information of the target object that is obtained when the target object interacts with the companion object; extracting, by the robot, an emotion feature quantity based on the emotion information, determining, based on the emotion feature quantity, an emotional pattern used by the target object to interact with the companion object, determining, based on the emotional pattern, a degree of interest of the target object in the companion object, extracting behavioral data of the companion object from the sensing information based on the degree of interest, and screening the behavioral data to obtain simulated object data; and simulating, by the robot, the companion object based on the simulated object data.

Robot, server, and human-machine interaction method

A content presentation method is used to intelligently present content to a user in different presentation modes according to different identified scenarios. The method includes acquiring, by an intelligent terminal, context data of a user; identifying a user use scenario according to the context data; determining a first presentation mode corresponding to the user use scenario; and presenting content to the user in the first presentation mode.

Content presentation method, content presentation mode push method, and intelligent terminal

Example video data processing methods and apparatus are disclosed. One example method includes receiving a first stream from a client, where the first bitstream is obtained by encoding image data in a specified spatial object. The specified spatial object is part of panoramic space, and a size of the specified spatial object is larger than a size of a spatial object of the panoramic space corresponding to viewport information. The spatial object corresponding to the viewport information is located in the specified spatial object. The client receives a second stream, where the second bitstream is obtained by encoding image data of a panoramic image of the panoramic space with a lower resolution than a resolution of the image data included in the specified spatial object. The client plays the second bitstream and first bitstream.

Video data processing method and apparatus

The present disclosure discloses a preview-image display while a terminal device photographs a picture. The method comprises: obtaining a first preview image and a second preview image, wherein the first preview image is generated based on a first photographing mode and the second preview image is generated based on a second photographing mode; and displaying a first part of the first preview image and a second part of the second preview image at the same time.

A wearable electronic device includes a sensor module, a processor, a display controller, and a display, where the sensor is configured to: collect data, generate a sensor signal that represents a feature of data of currently collected data, and send the sensor signal to the processor, the processor is configured to: determine, according to the received sensor signal, a manner to display that is corresponding to the feature of data represented by the sensor signal and is of the display, generate a display control signal, and send the display control signal to the display controller, and the display controller is configured to control, according to the display control signal, the display to display.

Wearable electronic device and display method of wearable electronic device according to sensor data

Embodiments of this application describe a motor vehicle self-driving method and a terminal device. The method may include obtaining, by a terminal device, vehicle external-environment data of a position of a motor vehicle and initial positioning precision of the motor vehicle. The method may also include determining, by the terminal device, a target driving parameter of the motor vehicle based on the vehicle external-environment data and the initial positioning precision. Furthermore, the method may include controlling, by the terminal device, the motor vehicle to drive based on the target driving parameter. In the embodiments of this application, the terminal device determines the target driving parameter of the motor vehicle based on the vehicle external-environment data and the initial positioning precision. In this way, the target driving parameter varies with the vehicle external-environment data, and further matches an external environment, thereby improving self-driving safety of the motor vehicle.

Motor vehicle self-driving method and terminal device

A motor vehicle self-driving method comprises obtaining a first positioning mode and a first driving route; obtaining second vehicle information of a second motor vehicle, where the second vehicle information includes a second positioning mode and a second driving route; determining whether the first driving route overlaps with the second driving route; when the first driving route overlaps with the second driving route, comparing positioning precision of the first positioning mode with positioning precision of the second positioning mode; determining a positioning mode with higher positioning precision in the first positioning mode and the second positioning mode as a target positioning mode; determining a target driving parameter based on the target positioning mode; and controlling the first motor vehicle and the second motor vehicle to drive based on the target driving parameter.

Self-driving motor vehicle and terminal with precision comparison

A method includes: parsing a bitstream to obtain an index value of a candidate motion vector list; constructing the candidate motion vector list, where the candidate motion vector list includes candidate motion vectors of K control points of a current block, the candidate motion vectors of the K control points are obtained based on a 2N-parameter affine transform model used for a neighboring block of the current block, N, K are integers greater than or equal to 2 and less than or equal to 4, and N is not equal to K; determining, in the candidate motion vector list, target candidate motion vectors of the K control points based on the index value; and obtaining a predicted motion vector of each subblock of the current block based on the target candidate motion vectors of the K control points. It helps improve coding efficiency in an audio and video coding process.

A content presentation method is used to intelligently present content to a user in different presentation modes according to different identified scenarios. The method includes acquiring, by an intelligent terminal, context data of a user, identifying a user use scenario according to the context data, determining a first presentation mode corresponding to the user use scenario, and presenting content to the user in the first presentation mode.

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Shenzhen, China

Jiali Fu