Abstract: A 3D scanning apparatus and method using lighting based on a smart phone. The 3D scanning apparatus includes: an image capturing unit for capturing the image of a 3D object using a camera and a lighting apparatus installed in a terminal; an image processing unit for generating a color-enhanced image corresponding to the light emitted by the lighting apparatus; and a scanning unit for scanning the 3D object in 3D by extracting a scan area from the color-enhanced image based on the light and by extracting position information corresponding to the scan area.

Abstract: An apparatus and method for measuring the position of a stereo camera. The apparatus for measuring a position of the camera according to an embodiment includes a feature point extraction unit for extracting feature points from images captured by a first camera and a second camera and generating a first feature point list based on the feature points, a feature point recognition unit for extracting feature points from images captured by the cameras after the cameras have moved, generating a second feature point list based on the feature points, and recognizing actual feature points based on the first feature point list and the second feature point list, and a position variation measurement unit for measuring variation in positions of the cameras based on variation in relative positions of the actual feature points.

Abstract: An apparatus and method for generating a 3D model, in which point clouds from a scanner are automatically aligned using marker information, with markers attached to an object. The apparatus includes a point cloud refinement unit for receiving point clouds and marker sets from scanning of an object, refining the point clouds, and transmitting refined point clouds and marker sets, a point cloud alignment unit for inquiring of a point cloud and marker set database about a point cloud group of point cloud pairs and a marker set group of marker set pairs, and aligning the point cloud group, wherein the point cloud pairs and the marker set pairs are acquired by scanning a single object in different directions, and a surface generation unit for generating a 3D model by reconstructing a surface of the object based on the aligned point cloud group.

Abstract: Method and apparatus for calibrating multiple cameras. A first mirror and a second mirror are arranged opposite each other. An object is disposed between the first mirror and the second mirror. Calibration of the multiple cameras is performed using a figure of the object formed on the second mirror via reflection from the first mirror and the second mirror.

Abstract: A 3D scanning apparatus and method using lighting based on a smart phone. The 3D scanning apparatus includes: an image capturing unit for capturing the image of a 3D object using a camera and a lighting apparatus installed in a terminal; an image processing unit for generating a color-enhanced image corresponding to the light emitted by the lighting apparatus; and a scanning unit for scanning the 3D object in 3D by extracting a scan area from the color-enhanced image based on the light and by extracting position information corresponding to the scan area.

Abstract: A method for calibrating a camera network includes generating a projection matrix by each of cameras in respect of a calibration pattern that is disposed at a plurality of different positions in a photography zone. A portion of the projection matrix is produced as a sub-projection matrix. Sub-projection matrixes are arranged widthwise and lengthwise to generate one sub-measurement matrix. A singular value decomposition (SVD) is performed on the sub-measurement matrix to change the sub-measurement matrix into a matrix having a rank of 3 and a SVD is performed on the changed sub-measurement matrix. A rotation value of the calibration pattern, and an internal parameter and a rotation value of each camera are extracted to thereby calibrate the camera network.

Abstract: 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.

Abstract: Disclosed is a method of calibrating a depth image based on a relationship between a depth sensor and a color camera, and an apparatus for calibrating a depth image may include a three-dimensional (3D) point determiner to determine a 3D point of a camera image and a 3D point of a depth image simultaneously captured with the camera image, a calibration information determiner to determine calibration information for calibrating an error of a depth image captured by the depth sensor and a geometric information between the depth sensor and a color camera, using the 3D point of the camera image and the 3D point of the depth image, and a depth image calibrator to calibrate the depth image based on the calibration information and the 3D point of the depth image.

Abstract: Provided are a multi-primitive fitting method including an acquiring point cloud data by collecting data of each of input points, a obtaining a segment for the points using the point cloud data, and a performing primitive fitting using data of points included in the segment and the point cloud data, and a multi-primitive fitting device that performs the method.

Abstract: Provided is an apparatus and method for extracting a movement path, the movement path extracting apparatus including an image receiver to receive an image from a camera group in which a mutual positional relationship among cameras is fixed, a geographic coordinates receiver to receive geographic coordinates of a moving object on which the camera group is fixed, and a movement path extractor to extract a movement path of the camera group based on a direction and a position of a reference camera of the camera group using the image and the geographic coordinates.

Abstract: A primitive fitting apparatus is provided. The primitive fitting apparatus may include a selecting unit to receive, from a user, a selection of points used to fit a primitive a user desires to fit from a point cloud, an identifying unit to receive a selection of the primitive from the user and to identify the selected primitive, and a fitting unit to fit the primitive to correspond to the points, using the points and primitive.

Abstract: A view image providing device and method are provided. The view image providing device may include a panorama image generation unit to generate a panorama image using a cube map including a margin area by obtaining an omnidirectional image, a mesh information generation unit to generate 3-dimensional (3D) mesh information that uses the panorama image as a texture by obtaining 3D data, and a user data rendering unit to render the panorama image and the mesh information into user data according to a position and direction input by a user.

Abstract: Disclosed is a method of calibrating a depth image based on a relationship between a depth sensor and a color camera, and an apparatus for calibrating a depth image may include a three-dimensional (3D) point determiner to determine a 3D point of a camera image and a 3D point of a depth image simultaneously captured with the camera image, a calibration information determiner to determine calibration information for calibrating an error of a depth image captured by the depth sensor and a geometric information between the depth sensor and a color camera, using the 3D point of the camera image and the 3D point of the depth image, and a depth image calibrator to calibrate the depth image based on the calibration information and the 3D point of the depth image.

Abstract: 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.

Abstract: An apparatus for calibrating images between cameras, includes: a detector for detecting dynamic markers from images taken by a motion capture camera and a video camera; a 3D position recovery unit for recovering 3D position data of the dynamic markers obtained by the motion capture camera; a 2D position tracking unit for tracking 2D position data of the dynamic markers obtained by the video camera; a matching unit for matching the 3D position data and the 2D position data of the dynamic markers; and a calibrating unit for converting the 3D position of the dynamic markers on a spatial coordinate system into image coordinates on an image coordinate system of the video camera to calculate intrinsic parameters and extrinsic parameters of the video camera to minimize a difference between coordinates of the 2D position data and the image coordinates.

Abstract: A method for restoration of building structure using infinity homographies calculated based on parallelograms includes: calculating, using two or more parallelograms, an infinity homography between those cameras which refer to an arbitrary camera; restoring cameras and the building structure on an affine space using the computed infinity homography and homologous points between images; and transforming the restored result onto the metric space using constraints on orthogonality of vectors joining the restored three-dimensional points, the ratio of lengths of the vectors and intrinsic camera parameters. As a result, intrinsic camera parameters, camera positions on the metric space and the structure of the building are restored. All the restoration is possible even when intrinsic camera parameters corresponding to all the images are not constant.

Abstract: A method for automated detection of feature for calibration is provided, which includes capturing images of a polyhedral structure including a plurality of rectangular planes and triangular planes in different directions through a plurality of cameras, and generating a plurality of image files, each of the rectangular planes having calibration objects formed thereon to be used as input values of a calibration engine, and each of the triangular planes having a marker formed thereon to grasp absolute and relative relationships between the rectangular planes; searching for the calibration objects in the image files; searching for the same plane in which the calibration objects are formed using the calibration objects; and indexing the respective calibration objects formed on the same plane.

Abstract: A method for calibrating a camera network includes generating a projection matrix by each of cameras in respect of a calibration pattern that is disposed at a plurality of different positions in a photography zone. A portion of the projection matrix is produced as a sub-projection matrix. Sub-projection matrixes are arranged widthwise and lengthwise to generate one sub-measurement matrix. A singular value decomposition (SVD) is performed on the sub-measurement matrix to change the sub-measurement matrix into a matrix having a rank of 3 and a SVD is performed on the changed sub-measurement matrix. A rotation value of the calibration pattern, and an internal parameter and a rotation value of each camera are extracted to thereby calibrate the camera network.

Abstract: A camera tracking apparatus for calculating in real time feature information and camera motion information based on an input image includes a global camera tracking unit for computing a global feature map having feature information on entire feature points; a local camera tracking unit for computing in real time a local feature map having feature information on a part of the entire feature points; a global feature map update unit for receiving the computed feature information from the global and local camera tracking units to update the global feature map; and a local feature selection unit for receiving the updated feature information from the global feature map update unit to select in real time the feature points contained in the local feature map. The local camera tracking unit computes the local feature map for each frame, while the global camera tracking unit computes the global feature map over frames.

Abstract: 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.