Abstract: A method of initially estimating a front view portion of a photographed image and separating the photographed image into a front view and a background without user interaction and apparatus performing the method are provided. The method of separating a front view and a background of an image includes dividing one or more pixels included in a photographed image into pixel groups according to color similarity between the pixels, estimating the position of the front view in the image divided into the pixel groups, and separating the front view and the background based on the estimated position of the front view. The method automatically separates the front view and the background of the image without a user input.

Abstract: An object pose recognition apparatus and method. The object pose recognition method includes acquiring first image data of an object to be recognized and 3-dimensional (3D) point cloud data of the first image data, and storing the first image data and the 3D point cloud data in a database, receiving input image data of the object photographed by a camera, extracting feature points from the stored first image data and the input image data, matching the stored 3D point cloud data and the input image data based on the extracted feature points and calculating a pose of the photographed object, and shifting the 3D point cloud data based on the calculated pose of the object, restoring second image data based on the shifted 3D point cloud data, and re-calculating the pose of the object using the restored second image data and the input image data.

Abstract: An image processing apparatus for searching for a feature point by use of a depth image and a method thereof are provided. The image processing apparatus includes an input unit configured to input a three-dimensional image having depth information, a feature point extraction unit configured to obtain a designated point from an object image extracted from the depth image to obtain a feature point that is located at a substantially farthest distance from the designated point, and to obtain other feature points that are located at substantially farthest distances from feature points that are previously obtained as well as the designated point. The apparatus includes a control unit configured to control the input unit and the feature point extraction unit so that time in estimating a structure of the object is reduced, and a recognition result is enhanced.

Abstract: An apparatus and a method for pose recognition, the method for pose recognition including generating a model of a human body in a virtual space, predicting a next pose of the model of the human body based on a state vector having an angle and an angular velocity of each part of the human body as a state variable, predicting a depth image about the predicted pose, and recognizing a pose of a human in a depth image captured in practice, based on a similarity between the predicted depth image and the depth image captured in practice, wherein the next pose is predicted based on the state vector having an angular velocity as a state variable, thereby reducing the number of pose samples to be generated and improving the pose recognition speed.

Abstract: A character recognition device to recognize characters after preprocessing an input image corrects distortion. The character recognition device includes an image input unit to receive an image acquired by an image device, a character position estimator to calculate a probability value of a position of characters of the image to estimate the position of the characters, an image preprocessor to detect a plurality of edges including the characters from the image and to correct distortion of the edges, and a character recognizer to recognize the characters included in a rectangle formed by the plurality of edges.

Abstract: A method of separating an object in a three dimension point cloud including acquiring a three dimension point cloud image on an object using an image acquirer, eliminating an outlier from the three dimension point cloud image using a controller, eliminating a plane surface area from the three dimension point cloud image, of which the outlier has been eliminated using the controller, and clustering points of an individual object from the three dimension point cloud image, of which the plane surface area has been eliminated using the controller.

Abstract: A method of initially estimating a front view portion of a photographed image and separating the photographed image into a front view and a background without user interaction and apparatus performing the method are provided. The method of separating a front view and a background of an image includes dividing one or more pixels included in a photographed image into pixel groups according to color similarity between the pixels, estimating the position of the front view in the image divided into the pixel groups, and separating the front view and the background based on the estimated position of the front view. The method automatically separates the front view and the background of the image without a user input.

Abstract: An object pose recognition apparatus and method. The object pose recognition method includes acquiring first image data of an object to be recognized and 3-dimensional (3D) point cloud data of the first image data, and storing the first image data and the 3D point cloud data in a database, receiving input image data of the object photographed by a camera, extracting feature points from the stored first image data and the input image data, matching the stored 3D point cloud data and the input image data based on the extracted feature points and calculating a pose of the photographed object, and shifting the 3D point cloud data based on the calculated pose of the object, restoring second image data based on the shifted 3D point cloud data, and re-calculating the pose of the object using the restored second image data and the input image data.

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 character recognition device to recognize characters after preprocessing an input image corrects distortion. The character recognition device includes an image input unit to receive an image acquired by an image device, a character position estimator to calculate a probability value of a position of characters of the image to estimate the position of the characters, an image preprocessor to detect a plurality of edges including the characters from the image and to correct distortion of the edges, and a character recognizer to recognize the characters included in a rectangle formed by the plurality of edges.