Samsung Electronics Co., Ltd.

University of Seoul Industry Cooperation Foundation

Lg Electronics Inc.

Electronics and Telecommunications Research Institute

Kichul Kim

Hongseok Lee

Yongkyu Kim

Hojung Kim

Myungjae Jeon

Sungbin Jin

Sunyoung Lee

Jaeyung Yeo

Sungho Kang

Bonyoung Koo

Han Ki Lee

Youngkyu Kim

Jaeyoung Park

Donggeun Lee

Changyong Jeong

Jisun Choi

Jooyong Byeon

Hyekwan Yun

Min Soo Kim

Hanmei Choi

Namseop Kwon

Bongjin Kuh

Jongha Park

Dae Sung Moon

Hyunsik Park

Sung Bum Pan

Yeseul Lee

Sunghwan Baek

Seolhee Kim

Dongyun Lee

Eunchung Noh

Youngtae Jin

Joonghan Shin

San Ha Kim

Jongsung Lim

Jeehun Ha

Yoonjae Park

JeongMeung Kim

Joonil Lee

HoJung Kim

Jongkun Kim

Youngwha Chung

Sunha Jeon

Soowon Jang

Hyunwook Ji

Byungkeon Park

San Kim

Moonyoung Woo

Sunmuk Choi

An apparatus for accelerating simultaneous localization and mapping (SLAM) includes a SLAM processor including a front-end processor and a back-end processor. The front-end processor is configured to track a position of a first feature, among features extracted from a first frame, in a second frame subsequent to the first frame, and the back-end processor is configured to obtain a first measurement regarding a map point and a camera pose of the first feature based on the position of the first feature in the second frame tracked by the front-end processor, compute elements affecting an optimization matrix in relation to the first measurement, among elements of a Hessian matrix regarding the map point and the camera pose, and accumulate the computed elements in the optimization matrix used to perform an optimization operation with respect to states of the map point and the camera pose.

Apparatus for accelerating simultaneous localization and mapping and electronic device including the same

An electronic device is disclosed that, in response to at least one of an utterance intent and a control target device not being identified from utterance data, classifies a situation factor based on the utterance data, determines one or more external devices that match the classified situation factor, and generates and presents to the user terminal one or more action scenarios for one or more external devices determined for the classified situation factor.

Electronic device and method to control external apparatus

An electronic device is provided and includes a processor and a memory operatively connected to the processor. The memory stores instructions that cause, when executed, the processor to acquire a first assistant result including data indicative of a first intent understood from an utterance of a first user, data indicative of an attribute of the utterance, first information provided to a terminal of the first user as a response of an artificial intelligence (AI) agent to the utterance, and a first parameter indicative of an attribute of the first information, to recognize the utterance as an information request utterance, based on the first intent and the attribute, and to track second information to be provided to the first user terminal as update information for the first information, based on the utterance being recognized as the information request utterance and the first parameter being identified as a specified type.

Electronic device for providing update information through an artificial intelligence agent service

Provided is an accelerator provided in an electronic device and configured to perform simultaneous localization and mapping (SLAM), the accelerator including a factor graph database, a memory, and a back-end processor, wherein the back-end processor is configured to receive a first piece of data corresponding to map points and camera positions from the factor graph database, convert the received first piece of data into a matrix for the map points and a matrix for the camera positions, store, in the memory, results obtained by performing an optimization calculation on the matrix for the map points and a matrix for at least one camera position, among the camera positions, corresponding to the map points, and obtain a second piece of data optimized with respect to the first piece of data based on the results stored in the memory.

Method for performing simultaneous localization and mapping and device using same

According to an embodiment, an electronic device comprises: a memory, a communication module comprising communication circuitry, and a processor operatively connected with the memory and the communication module. The processor is configured to control the electronic device to: obtain a utterance text corresponding to utterance speech, obtain an intent of the utterance text and emotion information based on the utterance speech and the utterance text, obtain a response text for the utterance text based on the intent of the utterance text and the emotion information, obtain a markup language including information about an output unit of text of the response text based on at least one of the intent of the utterance text, the emotion information, or the response text, and add the markup language to the response text and provide the response text. The text output unit is at least one selected from among a phoneme unit, a consonant and vowel unit, a syllable unit, or a word unit. A text output method in an artificial intelligence virtual assistant service of an electronic device may be performed using an artificial intelligence model.

Method for outputting text in artificial intelligence virtual assistant service and electronic device for supporting the same

A preconditioned conjugate gradient (PCG) solver, embedded in an electronic device to perform a simultaneous localization and mapping (SLAM) operation, includes an image database, a factor graph database, and a back-end processor, wherein the back-end processor is configured to receive an image from the image database to perform re-localization, receive, from the factor graph database, data for calculating six degrees of freedom (DoF)-related components, construct a matrix including the six degrees of freedom-related components based on the received data, and load and rearrange the matrix and a vector, to perform calculation on each block of each row of the matrix and the vector, then output first data, and shift second data to a location of the first data.

Method of accelerating simultaneous localization and mapping (SLAM) and device using same

A method and apparatus for processing hologram image data capable of optimizing image quality of a hologram image are provided. The image processing method includes receiving input image data, reading a header included at a predetermined location in the input image data, and generating hologram data configured to display a hologram image by performing a Fourier calculation and pixel encoding on the input image data based on at least one parameter recorded in the header, wherein the at least one parameter recorded in the header includes at least one of depth information, scale information, and gamma information.

Method and apparatus for processing hologram image data

An image processing method and apparatus are provided. The image processing apparatus includes a receiver configured to receive image data; and a processor configured to generate first data by performing a Fourier calculation on the received image data, generate second data by performing prism phase computation on the first data, generate third data by adding the first data and the second data, and perform encoding based on the third data.

Disclosed are a signal processing device and an image display apparatus including the same. The signal processing device and an image display apparatus including the same include: a converter configured to convert of frequency of an input stereo audio signal; a primary component analyzer configured to perform primary component analysis based on a signal from the converter; a feature extractor configured to extract a feature of a primary component signal based on a signal from the primary component analyzer; an envelope adjustor configured to perform envelope adjustment based on prediction performed on the basis of a deep neural network model; and an inverse converter configured to inversely convert a signal from the envelope adjustor to output an upmix audio signal of multi-channel. Accordingly, when upmixing the downmix stereo audio signal to a multichannel audio signal, spatial distortion can be improved.

Signal processing device and image display apparatus including the same

With regard to image data processing, a method of obtaining a focus term by using periodicity of the focus term is provided. The focus term may be used in a plurality of operation processes for processing image data.

Image data processing method and apparatus

A method and apparatus for processing image data are provided. An image data processing apparatus includes: a receiver configured to receive image data that represents a current frame; and a processor configured to perform an inverse fast Fourier Transform (IFFT) computation with respect to a first region of the current frame, and to obtain an IFFT computation result with respect to a second region of the current frame by using a result of the IFFT computation with respect to the first region.

Apparatus and method of processing image data using IFFT

A method of obtaining a focus term by using a periodicity of the focus term is provided. The focus term may be used in a plurality of operation processes for processing image data.

An image processing system for processing image data includes an image processing apparatus configured to process the image data to generate a hologram image; and a first memory and a second memory that store the image data. The image processing apparatus performs a first process and a second process in parallel, wherein the first process includes reading first data from the first memory and writing the first data to the second memory, and the second process includes reading second data from the second memory and writing the second data to the first memory.

Method and apparatus for processing image

A method and apparatus for converting first image data corresponding to a first depth and second image data corresponding to a second depth may be used for displaying a 3D image represented by the first image data and the second image data and performing FFT on the converted first image data and the converted second image data.

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Seoul, South Korea

Kichul Kim