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An Open Pose-based monocular camera gesture language recognition method

A recognition method and sign language technology, applied in character and pattern recognition, computer components, instruments, etc., can solve the problems of complex process, inaccuracy, and poor accuracy of recognition semantics, and achieve simple process, accurate feature extraction, and high accuracy Effect

Active Publication Date: 2018-09-14
SOUTHEAST UNIV
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Problems solved by technology

[0003] Purpose of the invention: The purpose of the present invention is to provide a monocular camera sign language recognition method based on OpenPose to solve the problems of inaccurate feature extraction, complicated process and poor accuracy of recognition semantics in existing sign language recognition methods

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  • An Open Pose-based monocular camera gesture language recognition method
  • An Open Pose-based monocular camera gesture language recognition method
  • An Open Pose-based monocular camera gesture language recognition method

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Embodiment Construction

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] Such as Figure 1-4 As shown, a monocular camera sign language recognition method based on OpenPose, including feature extraction and semantic recognition, the first step of feature extraction is: use a monocular camera to collect video data of the sign language of the demonstrator, and the collected video data is input into the OpenPose system , initially extract feature data of n*60*3 dimensions, save it as a json format file, extract 60 feature points from a frame of pictures, among them, select 44 feature points for the number of frames with n semantic actions, and recreate them with the neck as the origin Establish a coordinate system and perform normalization in the x-axis and y-axis directions to obtain n*44*2 final feature data. General body feature points select 6 feature points of wrist, elbow and shoulder. The hand feature points select three joints...

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Abstract

The invention provides an Open Pose-based monocular camera gesture language recognition method comprising the steps of collecting video data of gesture language of a presenter with a video camera; inputting the collected video data to an OpenPose system and primarily extracting three-dimensional characteristic data containing x-axis coordinates, y-axis coordinates and the confidence coefficient; selecting primarily extracted characteristic points, rebuilding a coordinate system with the neck as the origin, performing normalization in the x-axis direction and the y-axis direction to obtain final characteristic data; scanning the characteristic data by using three different granularities to obtain expansion characteristic data; inputting the expansion characteristic data to a deep forest model for multi-layer meaning recognition and obtaining recognition results of final meaning through an extreme classifier from the output of the last layer. The method has the capability of monocular vision recognition of gesture language, does not need big sample data and has the advantages of accurate characteristic extraction, simple process and high meaning recognition accuracy.

Description

technical field [0001] The invention relates to a sign language recognition method, in particular to an OpenPose-based monocular camera sign language recognition method. Background technique [0002] At present, the research in the field of sign language recognition mainly focuses on the recognition of isolated gestures. The information carriers of isolated gestures can be divided into two categories: one is the transmission of information by static hand gestures, and most sign languages ​​represented by letters belong to this category. , and the other is the transfer of information by the process of hand movement, including most of the sign languages ​​in modern sign language. The two contain information in space and time respectively. The key to isolated gesture recognition lies in feature extraction and semantic recognition. In terms of feature extraction, Chinese patent CN103246891A discloses a Kinect-based Chinese sign language recognition method, which can easily obtai...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/28G06V20/41
Inventor 薛启凡李煊鹏
Owner SOUTHEAST UNIV
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