Korea Electronics Technology Institute

Chang Jo Kim

Sang Ki Ko

Hye Dong Jung

Han Mu Park

A method and apparatus for recognizing a sign language or a gesture by using a three-dimensional (3D) Euclidean distance matrix (EDM) are disclosed. The method includes a two-dimensional (2D) EDM generation step for generating a 2D EDM including information about distances between feature points of a body recognized in image information by a 2D EDM generator, a 3D EDM generation step for receiving the 2D EDM and generating a 3D EDM by using a first deep learning neural network trained with training data in which input data is a 2D EDM and correct answer data is a 3D EDM by a 3D EDM generator, and a recognition step for recognizing a sign language or a gesture based on the 3D EDM.

Method and apparatus for recognizing sign language or gesture using 3D EDM

Disclosed is a method of providing a sign language video reflecting an appearance of a conversation partner. The method includes recognizing a speech language sentence from speech information, and recognizing an appearance image and a background image from video information. The method further comprises acquiring multiple pieces of word-joint information corresponding to the speech language sentence from joint information database, sequentially inputting the word-joint information to a deep learning neural network to generate sentence-joint information, generating a motion model on the basis of the sentence-joint information, and generating a sign language video in which the background image and the appearance image are synthesized with the motion model. The method provides a natural communication environment between a sign language user and a speech language user.

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Suwon-si, South Korea

Chang Jo Kim