Abstract:
A walk-assistive apparatus may include at least one joint that corresponds to at least one joint of a wearer, at least one link that connects the joint, and is rotated in response to rotation of the joint, a spring that is mounted in the link or the joint so that a length of the spring is changed in accordance with rotation of the link or the joint, and a processor that controls the change in the length of the spring to compensate for a weight by gravity when the wearer walks. Accordingly, the walk-assistive apparatus and a method of controlling the walk-assistive apparatus may use a mechanical element such as a spring to reduce energy, and weight compensation having uniform performance may be performed even in an arbitrary posture.
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:
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.
Abstract:
There is provided a method of controlling a wearable robot. The method includes measuring an electrical signal from a scalp of a wearer, estimating a current walking speed of the wearer using the measured electrical signal, and outputting assistive torque which allows the estimated current walking speed to approximate a target walking speed.
Abstract:
Provided are a walk-assistive robot and a method of controlling the same. The method of controlling the walk-assistive robot includes: obtaining ground information that is information regarding ground a walking direction; determining control patterns of the walk-assistive robot by analyzing the obtained ground information; and controlling the walk-assistive robot based on the determined control patterns.
Abstract:
A control method of a walking assist robot, may include: estimating a wearer's location on a map including walking environment information; determining a walking environment in a direction in which the wearer moves; and selecting a control mode for assisting the wearer's walking according to the walking environment.
Abstract:
An image processing apparatus and method may accurately separate only humans among moving objects, and also accurately separate even humans who have no motion via human segmentation using a depth data and face detection technology. The apparatus includes a face detecting unit to detect a human face in an input color image, a background model producing/updating unit to produce a background model using a depth data of an input first frame and face detection results, a candidate region extracting unit to produce a candidate region as a human body region by comparing the background model with a depth data of an input second or subsequent frame, and to extract a final candidate region by removing a region containing a moving object other than a human from the candidate region, and a human body region extracting unit to extract the human body region from the candidate region.
Abstract:
Disclosed herein are a multi-touch recognition apparatus and a control method thereof. The multi-touch recognition apparatus executes blur filtering for noise removal when an image is input through a camera unit photographing a screen of a display panel supporting multi-touch, calculates and outputs a difference image obtained by removing the background image stored in the storage unit from the blur-filtered image, calculates a new background image using the difference image and a binary image of the difference image, and updates the background image stored in the storage unit using the calculated new background image, thereby effectively removing a background other than multi-touch and thus improving multi-touch recognition performance.
Abstract:
Provided is a method of controlling a wearable robot, the method including: measuring a ground reaction force (GRF) exerted on a wearer's soles; calculating a time variation rate of the measured GRF; measuring the wearer's knee joint angle; and detecting a time point at which the calculated time variation rate of the GRF and the measured knee joint angle cross each other.
Abstract:
Disclosed herein are a multi-touch recognition apparatus and a control method thereof. The multi-touch recognition apparatus executes blur filtering for noise removal when an image is input through a camera unit photographing a screen of a display panel supporting multi-touch, calculates and outputs a difference image obtained by removing the background image stored in the storage unit from the blur-filtered image, calculates a new background image using the difference image and a binary image of the difference image, and updates the background image stored in the storage unit using the calculated new background image, thereby effectively removing a background other than multi-touch and thus improving multi-touch recognition performance.