Electronics and Telecommunications Research Institute

Industry-university Cooperation Foundation Hanyang University

Kap Kee Kim

Bon Woo Hwang

Bon Ki Koo

Ji Hyung Lee

Jin Sung Choi

Seung Wook Lee

Ho Won Kim

Jeon Gue Park

Hoon Chung

Chang Woo Chu

Jin Seo Kim

Byung Ok Kang

Il Kyu Park

Sung Joo Lee

Seong Jae Lim

Jeom Ja Kang

Seung Uk Yoon

Chang Joon Park

Ji Young Park

Ho Young Jung

Yun Keun Lee

Young Jik Lee

Euee Seon Jang

Seung-Uk Yoon

Jeung Chul Park

Ho-Young Jung

Bonki Koo

Yunkeun Lee

Hyung-Bae Jeon

Hyung Bae Jeon

Gil Haeng Lee

Yoon-Seok Choi

Hye Ryeong Jun

Kyoung Soo Son

Daiyong Kim

Byoungjun Kim

Jaebum Jun

Giseok Son

Hoon Young Cho

Hoon-Young Cho

Disclosed is a method of detecting and correcting an error in a 3D mesh model. According to the present disclosure, the method includes: determining at least one mesh on the basis of half-edge information; setting at least one cluster including the at least one mesh, on the basis of normal vector information on the at least one mesh; detecting a flip error of the at least one cluster; and correcting the at least one mesh in the at least one cluster in which the flip error is detected.

Method of detecting and correcting error in mesh and apparatus for same

Provided is a method and apparatus for reconstructing a three-dimensional (3D) face based on a stereo camera, the method including: acquiring n images of a target by controlling a plurality of stereo cameras in response to an image acquirement request, wherein n denotes a natural number; extracting n face regions from the n images, respectively; and reconstructing a viewpoint-based face image based on the n face regions.

Method and apparatus for reconstructing 3D face with stereo camera

The present invention provides a local multi-resolution 3-D face-inherent model generation apparatus, including one or more 3-D facial model generation cameras for photographing a face of an object at various angles in order to obtain one or more 3-D face models, a 3-D face-inherent model generation unit for generating a 3-D face-inherent model by composing the one or more 3-D face models, a local photographing camera for photographing a local part of the face of the object, a control unit for controlling the position of the local photographing camera on the 3-D face-inherent model, and a local multi-resolution 3-D face-inherent model generation unit for generating a local multi-resolution face-inherent model by composing an image captured by the local photographing camera and the 3-D face-inherent model, a local multi-resolution 3-D face-inherent model generation using the local multi-resolution 3-D face-inherent model generation apparatus, and a skin management system.

Local multi-resolution 3-D face-inherent model generation apparatus and method and facial skin management system

A system for managing face data includes a global face capturing unit configured to capture a global face image; and a global face data generation unit configured to obtain shape information and texture information of global face data, and generate the global face data. Further, the system includes a local face capturing unit configured to capture a plurality of local face images; and a global face posture extraction unit configured to estimate a position and a direction of the face of a captured user. Furthermore, the system includes a local capturing device posture extraction unit configured to extract posture information of the local face capturing unit; and a local face data generation unit configured to generate texture information and shape information, and generate local face data.

System and method for managing face data

Embodiments of the present invention provide methods and apparatuses for segmenting multi-view images into foreground and background based on a codebook. For example, in some embodiments, an apparatus is provided that includes: (a) a background model generation unit for extracting a codebook from multi-view background images and generating codeword mapping tables operating in conjunction with the codebook; and (b) a foreground and background segmentation unit for segmenting multi-view images into foreground and background using the codebook and the codeword mapping tables.

Method and apparatus for segmenting multi-view images into foreground and background based on codebook

An apparatus for 3D mesh compression based on quantization, includes a data analyzing unit () for decomposing data of an input 3D mesh model into vertices information () property information () representing property of the 3D mesh model, and connectivity information () between vertices constituting the 3D mesh model: and a mesh model quantizing unit () for producing quantized vertices and property information of the 3D mesh model by using the vertices, property and connectivity information (). Further, the apparatus for 3D mesh compression based on quantization includes a decision bit encoding unit () for calculating a decision bit by using the quantized connectivity information and then encoding the quantized vertex information, property information and connectivity information () by using the decision bit.

Method and apparatus for real time 3D mesh compression, based on quanitzation

Disclosed herein is an apparatus and method for separating a foreground and a background. The apparatus includes a background model creation unit for creating a code book including a plurality of code words in order to separate the foreground and the background, and a foreground/background separation unit for separating the foreground and the background using the created code book. The method includes the steps of creating a code book including a plurality of code words in order to separate the foreground and the background, rearranging the cord words of the created code book on the basis of the number of sample data that belong to each of the code words, and separating the foreground and the background using the code book.

Apparatus and method for separating foreground and background

A microphone-array-based speech recognition system using a blind source separation (BBS) and a target speech extraction method in the system are provided. The speech recognition system performs an independent component analysis (ICA) to separate mixed signals input through a plurality of microphone into sound-source signals, extracts one target speech spoken for speech recognition from the separated sound-source signals by using a Gaussian mixture model (GMM) or a hidden Markov Model (HMM), and automatically recognizes a desired speech from the extracted target speech. Accordingly, it is possible to obtain a high speech recognition rate even in a noise environment.

Microphone array based speech recognition system and target speech extracting method of the system

An apparatus for evaluating the performance of speech recognition includes a speech database for storing N-number of test speech signals for evaluation. A speech recognizer is located in an actual environment and executes the speech recognition of the test speech signals reproduced using a loud speaker from the speech database in the actual environment to produce speech recognition results. A performance evaluation module evaluates the performance of the speech recognition by comparing correct recognition results answers with the speech recognition results.

Apparatus and method for evaluating performance of speech recognition

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Daejeon, South Korea

Kap Kee Kim