Abstract: Disclosed herein is a computer-readable medium and method of a mobile platform detecting and tracking dynamic objects in an environment having the dynamic objects. The mobile platform acquires a three-dimensional (3D) image using a time-of-flight (TOF) sensor, removes a floor plane from the acquired 3D image using a random sample consensus (RANSAC) algorithm, and individually separates objects from the 3D image. Movement of the respective separated objects is estimated using a joint probability data association filter (JPDAF).

Abstract: An augmented reality (AR) service apparatus includes a camera to capture an actual image, a controller to receive feature point information about the captured image from at least one of a plurality of base stations (BSs), detect a location of the camera by matching data of feature points with data of the image, and provide location-based information in a same direction as the captured image according to the location of the camera, and a display to realize an AR service by combining the captured image with the location-based information under control of the controller.

Abstract: Disclosed herein are a method and apparatus for extracting feature points using hierarchical image segmentation and an image based localization method using the extracted feature points. An image is segmented using an affinity degree obtained using information observed during position estimation, new feature points are extracted from segmented areas in which registered feature points are not included, and position estimation is performed based on the new feature points. Accordingly, stable and reliable localization may be performed.

Abstract: An image-based localization feature point registration apparatus includes a camera to capture an image, a feature point extractor to extract a feature point from the captured image, a calculator to calculate depth information about the feature point according to whether the feature point is one of two-dimensional (2D) and a three-dimensional (3D) corner, and a feature point register to register 3D coordinates of the feature point based on the depth information about the feature point and image coordinates of the feature point.

Abstract: A volume cell (VOXEL) map generation apparatus includes an inertia measurement unit to calculate inertia information by calculating inertia of a volume cell (VOXEL) map generator, a Time of Flight (TOF) camera to capture an image of an object, thereby generating a depth image of the object and a black-and-white image of the object, an estimation unit to calculate position and posture information of the VOXEL map generator by performing an Iterative Closest Point (ICP) algorithm on the basis of the depth image of the object, and to recursively estimate a position and posture of the VOXEL map generator on the basis of VOXEL map generator inertia information calculated by the inertia measurement unit and VOXEL map generator position and posture information calculated by the ICP algorithm, and a grid map construction unit to configure a grid map based on the recursively estimated VOXEL map generator position and posture.

Abstract: Two-dimensional image information and three-dimensional image information of a subject are acquired, facial recognition is performed using the two-dimensional image information to determine whether a recognized face is a registered user's face, an elliptical model of the user is matched to the three-dimensional image information to calculate an error if it is determined that the recognized face is the user's face, and it is determined whether the user's face is improperly used based on the error. The subject's face is determined using the two-dimensional image information and the three-dimensional image information of the subject and it is determined whether the recognized face is improperly used, thereby improving facial recognition reliability. Thus, information security is improved.

Abstract: Disclosed herein is a method of building a map of a mobile platform moving in a dynamic environment and detecting an object using a 3D camera sensor, e.g., an IR TOF camera sensor, for localization. A localization technology to separate and map a dynamic object and a static object is applied to a mobile platform, such as an unmanned vehicle or a mobile robot. Consequently, the present method is capable of accurately building map information based on the static object in a dynamic environment having a large number of dynamic objects and achieving a dynamic object avoidance or chasing function using position information acquired to build the map.

Abstract: A semiconductor device and a method for manufacturing the same are disclosed, which can prevent a short-circuit between a bit line contact plug and a storage node contact plug, resulting in improved semiconductor device characteristics. A method for manufacturing a semiconductor device includes: forming a bit line contact hole from which an active region is protruded, by etching a semiconductor substrate; forming a conductive material over the semiconductor substrate including the bit line contact hole; etching the conductive material to form a bit line contact plug and a bit line, each of which has a smaller width than the bit line contact hole; and forming a spacer insulation film over the entire surface of the semiconductor substrate including the bit line contact hole, the bit line contact plug, and the bit line.

Abstract: A walking robot and a simultaneous localization and mapping method thereof in which odometry data acquired during movement of the walking robot are applied to image-based SLAM technology so as to improve accuracy and convergence of localization of the walking robot. The simultaneous localization and mapping method includes acquiring image data of a space about which the walking robot walks and rotational angle data of rotary joints relating to walking of the walking robot, calculating odometry data using kinematic data of respective links constituting the walking robot and the rotational angle data, and localizing the walking robot and mapping the space about which the walking robot walks using the image data and the odometry data.

Abstract: A system and method for extracting 3D coordinates, the method includes obtaining, by a stereoscopic image photographing unit, two images of a target object, and obtaining 3D coordinates of the object on the basis of coordinates of each pixel of the two images, measuring, by a Time of Flight (TOF) sensor unit, a value of a distance to the object, and obtaining 3D coordinates of the object on the basis of the measured distance value, mapping pixel coordinates of each image to the 3D coordinates obtained through the TOF sensor unit, and calibrating the mapped result, determining whether each set of pixel coordinates and the distance value to the object measured through the TOF sensor unit are present, calculating a disparity value on the basis of the distance value or the pixel coordinates, and calculating 3D coordinates of the object on the basis of the calculated disparity value.

Abstract: A volume cell (VOXEL) map generation apparatus includes an inertia measurement unit to calculate inertia information by calculating inertia of a volume cell (VOXEL) map generator, a Time of Flight (TOF) camera to capture an image of an object, thereby generating a depth image of the object and a black-and-white image of the object, an estimation unit to calculate position and posture information of the VOXEL map generator by performing an Iterative Closest Point (ICP) algorithm on the basis of the depth image of the object, and to recursively estimate a position and posture of the VOXEL map generator on the basis of VOXEL map generator inertia information calculated by the inertia measurement unit and VOXEL map generator position and posture information calculated by the ICP algorithm, and a grid map construction unit to configure a grid map based on the recursively estimated VOXEL map generator position and posture.

Abstract: A simultaneous localization and map building method of a mobile robot including an omni-directional camera. The method includes acquiring an omni-directional image from the omni-directional camera, dividing the obtained omni-directional image into upper and lower images according to a preset reference to generate a first image, which is the lower image, and a second image, which is the upper image, extracting feature points from the first image and calculating visual odometry information calculating visual odometry information to track locations of the extracted feature points based on a location of the omni-directional camera, and performing localization and map building of the mobile robot using the calculated visual odometry information and the second image as an input of an extended Kalman filter.

Abstract: A moving robot and a method to build a map for the same, wherein a 3D map for an ambient environment of the moving robot may be built using a Time of Flight (TOF) camera that may acquire 3D distance information in real time. The method acquires 3D distance information of an object present in a path along which the moving robot moves, accumulates the acquired 3D distance information to construct a map of a specific level and stores the map in a database, and then hierarchically matches maps stored in the database to build a 3D map for a set space. This method may quickly and accurately build a 3D map for an ambient environment of the moving robot.

Abstract: A 3D object tracking method and apparatus in which a model of an object to be tracked is divided into a plurality of polygonal planes and the object is tracked using texture data of the respective planes and geometric data between the respective planes to enable more precise tracking. The 3D object tracking method includes modeling the object to be tracked to generate a plurality of planes, and tracking the plurality of planes, respectively. The modeling of the object includes selecting points from among the plurality of planes, respectively, and calculating projective invariants using the selected points.

Abstract: A method of extracting a three-dimensional (3D) edge is based on a two-dimensional (2D) intensity image and a depth image acquired using a time of flight (TOF) camera. The 3D edge extraction method includes acquiring a 2D intensity image and a depth image using a TOF camera, acquiring a 2D edge image from the 2D intensity image, and extracting a 3D edge using a matched image obtained by matching the 2D intensity image and the depth image.

Abstract: An image-based localization feature point registration apparatus includes a camera to capture an image, a feature point extractor to extract a feature point from the captured image, a calculator to calculate depth information about the feature point according to whether the feature point is one of two-dimensional (2D) and a three-dimensional (3D) corner, and a feature point register to register 3D coordinates of the feature point based on the depth information about the feature point and image coordinates of the feature point.

Abstract: Two-dimensional image information and three-dimensional image information of a subject are acquired, facial recognition is performed using the two-dimensional image information to determine whether a recognized face is a registered user's face, an elliptical model of the user is matched to the three-dimensional image information to calculate an error if it is determined that the recognized face is the user's face, and it is determined whether the user's face is improperly used based on the error. The subject's face is determined using the two-dimensional image information and the three-dimensional image information of the subject and it is determined whether the recognized face is improperly used, thereby improving facial recognition reliability. Thus, information security is improved.

Abstract: An augmented reality (AR) service apparatus includes a camera to capture an actual image, a controller to receive feature point information about the captured image from at least one of a plurality of base stations (BSs), detect a location of the camera by matching data of feature points with data of the image, and provide location-based information in a same direction as the captured image according to the location of the camera, and a display to realize an AR service by combining the captured image with the location-based information under control of the controller.

Abstract: Disclosed herein is a computer-readable medium and method of a mobile platform detecting and tracking dynamic objects in an environment having the dynamic objects. The mobile platform acquires a three-dimensional (3D) image using a time-of-flight (TOF) sensor, removes a floor plane from the acquired 3D image using a random sample consensus (RANSAC) algorithm, and individually separates objects from the 3D image. Movement of the respective separated objects is estimated using a joint probability data association filter (JPDAF).

Abstract: Disclosed herein are a method and apparatus for extracting feature points using hierarchical image segmentation and an image based localization method using the extracted feature points. An image is segmented using an affinity degree obtained using information observed during position estimation, new feature points are extracted from segmented areas in which registered feature points are not included, and position estimation is performed based on the new feature points. Accordingly, stable and reliable localization may be performed.