Abstract:
An object recognition method, a descriptor generating method for object recognition, and a descriptor for object recognition capable of extracting feature points using the position relationship and color information relationship between points in a group that are sampled from an image of an object, and capable of recognizing the object using the feature points, the object recognition method including extracting feature components of a point cloud using the position information and the color information of the points that compose the point cloud of the three-dimensional (3D) image of an object, generating a descriptor configured to recognize the object using the extracted feature components; and performing the object recognition based on the descriptor.
Abstract:
An endoscope to acquire a 3D image and a wide view-angle image and an image processing apparatus using the endoscope includes a front image acquirer to acquire a front image and a lower image acquirer to acquire a lower image in a downward direction of the front image acquirer. The front image acquirer includes a first objective lens and a second objective lens arranged side by side in a horizontal direction. The lower image acquirer includes a third objective lens located below the first objective lens and inclined from the first objective lens and a fourth objective lens located below the second objective lens and inclined from the second objective lens.
Abstract:
A cleaning robot includes a data acquisition unit that acquires actual sensor data by measuring a distance from a current position to an object to be measured; a local map acquisition unit that acquires a local map by scanning the vicinity of the current position based on an environmental map stored in advance; and a processor that determines coordinates of the current position for the local map by performing matching between the local map and the actual sensor data, and determines a traveling direction based on the current position by calculating a main segment angle of a line segment existing in the local map.
Abstract:
An optical scanning probe and an apparatus to generate three-dimensional (3D) data using the same are provided. The apparatus to generate 3D data includes an optical scanning probe that scans light generated from a light emitter over an object to be measured, a distance calculation processor that calculates a distance between the optical scanning probe and the object to be measured, based on the light scanned over the object to be measured and light reflected from the object to be measured; and a depth image generation processor that generates 3D data based on a scanning direction of the optical scanning probe and the distance between the optical scanning probe and the object to be measured.
Abstract:
A robot cleaner includes a traveling unit to move a main body, an obstacle sensing unit to sense an obstacle, a light reception unit to receive modulated light according to a control command of a user, and a controller to control the traveling unit so that the main body traces a light spot formed by the light. If an obstacle is detected, the controller controls the traveling unit such that the main body traces an outline of the obstacle according to the light spot position and the obstacle position.
Abstract:
A robot cleaner and a method for controlling the same are disclosed. The robot cleaner includes: a main body; one or more infrared ray (IR) sensors configured to receive IR signals from a transmission device in various directions; a drive motor configured to move the main body toward the transmission device upon receiving a control signal from a controller; and a controller configured to remove reflected waves from among the plurality of IR signals by generating a transmission device direction estimation value, and control driving of the main body using the drive motor on the basis of the transmission device direction estimation value.
Abstract:
A robot that moves to a position indicated by a remote device, and a method for controlling the moving robot. The moving robot according to an embodiment includes a traveling unit that moves a main body, a light reception unit that receives light, and a control unit that determines a traveling direction of the moving robot by filtering the light received from the light reception unit in accordance with a probability-based filtering method, and controls the traveling unit so that the main body travels in the traveling direction.
Abstract:
Disclosed is a camera assembly having a wide viewing angle using a variable mirror. The camera assembly includes a variable mirror located in front of an image sensor, a variable mirror controller to switch a mode of the variable mirror to one of a reflection mode to reflect light incident upon the variable mirror and a transmission mode to transmit light incident upon the variable mirror, an image sensor to sense the light reflected by the variable mirror to acquire first image data and to sense the light transmitted through the variable mirror to acquire second image data, and an image processing unit to register the first image data and the second image data acquired by the image sensor to generate a third image.
Abstract:
Disclosed is a camera assembly having a wide viewing angle using a variable mirror. The camera assembly includes a variable mirror located in front of an image sensor, a variable mirror controller to switch a mode of the variable mirror to one of a reflection mode to reflect light incident upon the variable mirror and a transmission mode to transmit light incident upon the variable mirror, an image sensor to sense the light reflected by the variable mirror to acquire first image data and to sense the light transmitted through the variable mirror to acquire second image data, and an image processing unit to register the first image data and the second image data acquired by the image sensor to generate a third image.
Abstract:
A face recognition apparatus and face recognition method perform face recognition of a face by comparing an image of the face to be identified with target images for identification. The face recognition apparatus includes an image input unit to receive an image of a face to be identified, a sub-image production unit to produce a plurality of sub-images of the input face image using a plurality of different face models, a storage unit to store a plurality of target images, and a face recognition unit to set the sub-images to observed nodes of a Markov network, to set the target images to hidden nodes of the Markov network, and to recognize the presence of a target image corresponding to the face images to be identified using a first relationship between the observed nodes and the hidden nodes and a second relationship between the hidden nodes.