Electronics and Telecommunications Research Institute

Bon-Ki Koo

Chang-Woo Chu

Jin-Sung Choi

Ho-Won Kim

Seong-Jae Lim

Ji-Hyung Lee

Byoung-Tae Choi

Seung-Wook Lee

Hyun-Bin Kim

Seung-Uk Yoon

Jae-Hean Kim

Jae-Chul Kim

Han-Byul Joo

Bon-Woo Hwang

Kap-Kee Kim

Il-Kyu Park

Young-Mi Cha

Do-Hyung Kim

Chang-Joon Park

Hyun Joon Kang

Seong-Jin Park

Hae-Dong Kim

In-Su Jang

Hye-Ryeong Jun

Jea-Chul Kim

Sung-Ye Kim

Disclosed herein are an apparatus and method for calibrating an augmented-reality image. The apparatus includes a camera unit for capturing an image and measuring 3D information pertaining to the image, an augmented-reality image calibration unit for generating an augmented-reality image using the image and the 3D information and for calibrating the augmented-reality image, and a display unit for displaying the augmented-reality image.

Apparatus and method for calibrating augmented-reality image

Disclosed herein is a device and method for supporting 3D object printing and an apparatus for providing a 3D object printing service. A proposed device for supporting 3D object printing includes an information collection unit for collecting preference information of a user and performance information of a 3D printer. A download unit downloads a 3D model that is an object to be printed and model information defined in the 3D model in response to a printable selection signal. A model information creation unit creates new model information based on the 3D model and the model information defined in the 3D model. A print control command generation unit generates a print control command based on the preference information of the user and the performance information of the 3D printer, output from the information collection unit, and the new model information, output from the model information creation unit.

Device and method for supporting 3D object printing and apparatus for providing 3D object printing service

An image processing apparatus and method for calibrating a depth of a depth sensor. The image processing method may include obtaining a depth image of a target object captured by a depth sensor and a color image of the target object captured by a color camera; and calibrating a depth of the depth sensor by calibrating a geometrical relation between a projector and a depth camera, which are included in the depth sensor, based the obtained depth and color images and calculating a correct feature point on an image plane of the depth camera that corresponds to a feature point of an image plane of the projector.

Image processing method and apparatus for calibrating depth of depth sensor

Disclosed herein is an apparatus and method for automatically creating a 3D personalized figure suitable for 3D printing by detecting a face area and features for respective regions from face data acquired by heterogeneous sensors and by optimizing global/local transformation. The 3D personalized figure creation apparatus acquires face data of a user corresponding to a reconstruction target; extracts feature points for respective regions from the face data, and reconstructs unique 3D models of the user's face, based on the extracted feature points; creates 3D figure models based on the unique 3D models and previously stored facial expression models and body/adornment models; and verifies whether each 3D figure model has a structure and a shape corresponding to actual 3D printing, corrects and edits the 3D figure model based on results of verification, and outputs a 3D figure model corresponding to 3D printing.

Apparatus and method for creating three-dimensional personalized figure

Disclosed herein is an apparatus and method for extracting correspondences between aerial images. The apparatus includes a line extraction unit, a line direction determination unit, a building top area extraction unit, and a correspondence extraction unit. The line extraction unit extracts lines corresponding buildings from aerial images. The line direction determination unit defines the directions of the lines as x, y and z axis directions based on a two-dimensional (2D) coordinate system. The building top area extraction unit rotates lines in the x and y axis directions so that the lines are arranged in parallel with the horizontal and vertical directions of the 2D image, and then extracts building top areas from rectangles. The correspondence extraction unit extracts correspondences between the aerial images by comparing the locations of the building top areas extracted from the aerial images.

Apparatus and method for extracting correspondences between aerial images

Disclosed herein is technology for generating a digital clone. An apparatus for generating a digital clone includes a standard human body model generation unit for extracting information about appearance deformations based on joint control angles of joints from posture-based appearance deformation examples, generating a parametric shape control engine in which the appearance deformation information is incorporated, and incorporating the parametric shape control engine in a standard mesh-type human body model, thus generating a standard human body model. A unique human body model generation unit receives multi-view image examples based on a change in a posture of an actor, generates a 3D model of the actor based on multi-view image examples, and transfers the standard human body model to the 3D model, thus generating a unique human body model, in which unique appearance deformations of the actor based on the change in the posture of the actor are reflected.

Apparatus and method for generating digital clone

An apparatus includes: an input/output interface configured to have a reference surface model and a floating surface model inputted thereto; a memory having instructions for registration of the reference surface model and the floating surface model stored therein; and a processor configured for registration of the reference surface model and the floating surface model according to the instructions. The instructions perform: selecting initial transformation parameters corresponding to the floating surface model by comparing depth images of the reference surface model and the floating surface model; transforming the floating surface model according to the initial transformation parameters; calculating compensation transformation parameters through a matrix calculated by applying singular value decomposition to a cross covariance matrix between the reference surface model and the floating surface model; and transforming the floating surface model according to the compensation transformation parameters, and executing registration of the reference surface model and the floating surface model.

Apparatus and method for registration of surface models

Disclosed herein are an apparatus and method for reconstructing a three-dimensional (3D) face based on multiple cameras. The apparatus includes a multi-image analysis unit, a texture image separation unit, a reconstruction image automatic synchronization unit, a 3D appearance reconstruction unit, and a texture processing unit. The multi-image analysis unit determines the resolution information of images received from a plurality of cameras, and determines whether the images have been synchronized with each other. The texture image separation unit separates a texture processing image by comparing the resolutions of the received images. The reconstruction image automatic synchronization unit synchronizes images that are determined to be asynchronous images by the multi-image analysis unit. The 3D appearance reconstruction unit computes the 3D coordinate values of the synchronized images, and reconstructs a 3D appearance image. The texture processing unit reconstructs a 3D image by mapping the texture processing image to the 3D appearance image.

Apparatus and method for reconstructing three dimensional faces based on multiple cameras

Disclosed herein is an apparatus and method for estimating the joint structure of a human body. The apparatus includes a multi-view image acquisition unit for receiving multi-view images acquired by capturing a human body. A human body foreground separation unit extracts a foreground region corresponding to the human body from the acquired multi-view images. A human body shape restoration unit restores voxels indicating geometric space occupation information of the human body using the foreground region corresponding to the human body, thus generating voxel-based three-dimensional (3D) shape information of the human body. A skeleton information extraction unit generates 3D skeleton information from the generated voxel-based 3D shape information of the human body. A skeletal structure estimation unit estimates positions of respective joints from a skeletal structure of the human body using both the generated 3D skeleton information and anthropometric information.

Apparatus and method for estimating joint structure of human body

Disclosed herein is a 3D urban modeling apparatus and method. The 3D urban modeling apparatus includes a calibration unit for calibrating data about a translation and a rotation of at least one capturing device at a time that input aerial images and terrestrial images were captured. A building model generation unit generates at least one 3D building model based on the aerial images and the terrestrial images to which results of the calibration have been applied. A terrain model generation unit generates a 3D terrain model by converting an input digital elevation model into a 3D mesh. A texture extraction unit extracts textures related to the building model and the terrain model from the aerial images and the terrestrial images. A model matching unit generates a 3D urban model by matching the building model with the terrain model, which are based on the textures, with each other.

Three-dimensional urban modeling apparatus and method

Disclosed herein is a 3D model shape transformation apparatus. The 3D model shape transformation apparatus includes a camera unit, a shape restoration unit, a skeleton structure generation unit, and a skeleton transformation unit. The camera unit obtains a plurality of 2D images in a single frame by capturing the shape of an object. The shape restoration unit generates a 3D volume model by restoring the shape of the object based on the plurality of 2D images. The skeleton structure generation unit generates the skeleton structure of the 3D volume model. The skeleton transformation unit transforms the size and posture of the 3D volume model into those of a template model by matching the skeleton structure of the template model with the skeleton structure of the 3D volume model.

3D model shape transformation method and apparatus

Disclosed herein is a motion capture apparatus and method. The motion capture apparatus includes a three-dimensional (3D) appearance reconstruction unit for reconstructing a 3D appearance of an entity using a multi-view image obtained by capturing the entity at a T+1-th frame. A 3D skeleton generation unit generates a 3D skeleton of the T+1-th frame using the 3D appearance and a model of the entity having a motion of a T-th frame. A motion reconstruction unit reconstructs a motion of the T+1-th frame of the model by changing the motion of the model based on the 3D skeleton of the T+1-th frame.

Motion capture apparatus and method

The present invention relates to a method and apparatus for capturing a motion of a dynamic object, and restore appearance information of an object making a dynamic motion and motion information of main joints from multi-viewpoint video images of motion information of a dynamic object such as a human body, making a motion through a motion of a skeletal structure on the basis of the skeletal structure, acquired by using multiple cameras. According to the exemplary embodiments of the present invention, it is possible to restore motion information of the object making a dynamic motion by using only an image sensor for a visible light range and to reproduce a multi-viewpoint image by effectively storing the restored information. Further, it is possible to restore motion information of the dynamic object without attaching a specific marker.

Method and apparatus for capturing motion of dynamic object

Disclosed herein is a camera calibration apparatus. The camera calibration apparatus includes an image reception unit and a camera calibration unit. The image reception unit receives images, in which a same background is captured, from respective cameras placed at locations which are different from each other. The camera calibration unit calculates an entire matrix using canonic topographies for all parallelograms located on respective surfaces which are different from each other within each of the images, and calculates infinite hymnographies between the cameras using the entire matrix at the same time.

Camera calibration apparatus and method using parallelograms in image and multi-view control

Provided is an apparatus for reconstructing a 3D shape of an object by using Helmholtz stereopsis. The apparatus includes: an image capturer for capturing two pairs of images satisfying Helmholtz reciprocity condition; a preprocessor for estimating optical and geometrical characteristics of a camera used for the image capturing; and a geometrical data reconstructor for converting Helmholtz restrictions generated from the respective pairs of the images into partial differential equations on the basis of the estimated optical and geometrical characteristics, and reconstructing 3D surface data of an object with depth discontinuity at a boundary between regions on the basis of the partial differential equations.

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Daejeon, South Korea

Bon-Ki Koo