Abstract:
An electronic device and an method of the electronic device are provided, where the electronic device maintains a context that does not reflect a request for a secret conversation, in response to the request for the secret conversation being received from a first user, and generates a response signal to a voice signal of a second user based on the maintained context, in response to an end of the secret conversation with the first user.
Abstract:
A wearable device includes first and second electronic modules, a connection module configured to electrically connect the first electronic module to the second electronic module, and a length adjusting module of which length is adjustable to bring the connection module in contact with a user. The length adjusting module comprises first and second fastening units configured to be assembled and disassembled and configured to be locked together in a fastened position when assembled. When the first and second fastening units are assembled, the first fastening unit is electrically connected to the second fastening unit and a length of the length adjusting module is adjusted.
Abstract:
The present disclosure relates to signaling of sample adaptive offset (SAO) parameters determined to minimize an error between an original image and a reconstructed image in video encoding and decoding operations. An SAO decoding method includes obtaining context-encoded leftward SAO merge information and context-encoded upward SAO merge information from a bitstream of a largest coding unit (MCU); obtaining SAO on/off information context-encoded with respect to each color component, from the bitstream; if the SAO on/off information indicates to perform SAO operation, obtaining absolute offset value information for each SAO category bypass-encoded with respect to each color component, from the bitstream; and obtaining one of band position information and edge class information bypass-encoded with respect to each color component, from the bitstream.
Abstract:
A device and a method of unlocking a device are provided. The method of unlocking a device includes: determining whether an input tool of the device is separated from the device, when a disabled screen of the device is enabled; selecting one user interface from among a plurality of user inter faces for unlocking the device on the enabled screen of the device, based on the determination result; displaying the selected user interface on the screen of the device; and receiving a touch input with respect to the displayed user interface. The plurality of user interface include a user interface for receiving a touch input by the input tool and a user interface for receiving a touch input by a body part of a user
Abstract:
A method of generating a parameter set includes obtaining common information inserted into at least two lower parameter sets which belong to the same upper parameter set; determining whether the common information is to be added to at least one among the upper parameter set and the at least two lower parameter sets; and adding the common information to at least one among the upper parameter set and the at least two lower parameter sets, based on a result of the determining.
Abstract:
A multi-view video encoding method multiplexes an encoded multi-view image by a predetermined data unit and adds a scalable extension type (SET) indicating which view of image among a basic view image and an additional view image is related to data included in the predetermined data unit, a depth flag indicating which image is related to the data among a texture image and a depth map image, and a view ID of the data to a header of the predetermined data unit.
Abstract:
A method and apparatus for generating a 3K-resolution display image for a mobile terminal screen are disclosed. The method includes: receiving an input image; selecting a 3K resolution as a resolution of an image to be reproduced on the mobile terminal screen of a predetermined size, based on human cognitive characteristics and resolution analytical ability with respect to the mobile terminal screen; and generating a display image having the selected 3K resolution by using the input image.
Abstract:
Provided are methods and apparatuses for encoding and decoding an image. The method of encoding includes: determining a maximum size of a buffer to decode each image frame by a decoder, a number of image frames to be reordered, and latency information of an image frame having a largest difference between an encoding order and a display order from among image frames that form an image sequence, based on an encoding order the image frames that form the image sequence, an encoding order of reference frames referred to by the image frames, a display order of the image frames, and a display order of the reference frames; and adding, to a mandatory sequence parameter set, a first syntax indicating the maximum size of the buffer, a second syntax indicating the number of image frames to be reordered, and a third syntax indicating the latency information.
Abstract:
Methods of encoding and decoding multi-view video by performing inter-prediction and inter-view prediction on each of pictures of multi-view video according to views are provided. A prediction encoding method of encoding a multi-view video includes determining a reference picture set; determining at least one reference list between a first reference list and a second reference list; determining one reference picture and reference block for a current block of the current picture using the determined one reference list; and performing inter-prediction or inter-view prediction for the current block using the reference block.
Abstract:
Provided is a prediction image generating technology using a deep neural network (DNN). Provided is an image decoding method including: receiving a bitstream of an encoded image; determining at least one block split from the encoded image; determining neighboring blocks for predicting a current block among the at least one block; generating prediction data of the current block by applying the neighboring blocks to a DNN learning model configured to predict a block of an image by using at least one computer; extracting residual data of the current block from the bitstream; and reconstructing the current block by using the prediction data and the residual data.