Electronics and Telecommunications Research Institute

Young-Woo Yoon

Jae-Hong Kim

Min-Su Jang

Do-Hyung Kim

Jae-Yeon Lee

Jae-Il Cho

Jeong-Dan Choi

Ho-Sub Yoon

Kyu-Dae Ban

Woo-Ri Ko

Disclosed herein are an apparatus and method for evaluating a human motion using a mobile robot. The method may include identifying the exercise motion of a user by analyzing an image of the entire body of the user captured using a camera installed in the mobile robot, evaluating the pose of the user by comparing the standard pose of the identified exercise motion with images of the entire body of the user captured by the camera of the mobile robot from two or more target locations, and comprehensively evaluating the exercise motion of the user based on the pose evaluation information of the user from each of the two or more target locations.

Apparatus and method for evaluating human motion using mobile robot

Disclosed herein are an apparatus and method for generating robot interaction behavior. The method for generating robot interaction behavior includes generating co-speech gesture of a robot corresponding to utterance input of a user, generating a nonverbal behavior of the robot, that is a sequence of next joint positions of the robot, which are estimated from joint positions of the user and current joint positions of the robot based on a pre-trained neural network model for robot pose estimation, and generating a final behavior using at least one of the co-speech gesture and the nonverbal behavior.

Apparatus and method for generating robot interaction behavior

Disclosed herein are an apparatus for writing a motion script and an apparatus and method for self-teaching of a motion. The method for self-teaching of a motion, in which the apparatus for writing a motion script and the apparatus for self-teaching of a motion are used, includes creating, by the apparatus for writing a motion script, a motion script based on expert motion of a first user; analyzing, by the apparatus for self-teaching of a motion, a motion of a second user, who learns the expert motion, based on the motion script; and outputting, by the apparatus for self-teaching of a motion, a result of analysis of the motion of the second user.

Apparatus for writing motion script, apparatus for self-teaching of motion and method for using the same

Disclosed herein are an apparatus and method for determining the speech and motion properties of an interactive robot. The method for determining the speech and motion properties of an interactive robot includes receiving interlocutor conversation information including at least one of voice information and image information about an interlocutor that interacts with an interactive robot, extracting at least one of a verbal property and a nonverbal property of the interlocutor by analyzing the interlocutor conversation information, determining at least one of a speech property and a motion property of the interactive robot based on at least one of the verbal property, the nonverbal property, and context information inferred from a conversation between the interactive robot and the interlocutor, and controlling the operation of the interactive robot based on at least one of the determined speech property and motion property of the interactive robot.

Apparatus for determining speech properties and motion properties of interactive robot and method thereof

A face recognition technology using physiognomic feature information, which can improve the accuracy of face recognition. For this, the face recognition method using physiognomic feature information includes defining standard physiognomic types for respective facial elements, capturing a facial image of a user, detecting information about facial elements from the facial image, and calculating similarity scores relative to the standard physiognomic types for respective facial elements of the user based on the facial element information.

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Daejeon, South Korea

Young-Woo Yoon