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Human skeleton point parameter acquisition device applied to humanoid motion mimicry and recognition method thereof

A technology of human body movement and human body, applied in character and pattern recognition, image data processing, instruments, etc., can solve the problems of low recognition accuracy and poor real-time performance, and achieve high recognition accuracy, strong real-time performance and strong robustness Effect

Pending Publication Date: 2017-07-25
江西制造职业技术学院
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Problems solved by technology

[0004] Aiming at the problems of low recognition accuracy and poor real-time performance caused by environmental interference in posture recognition, the present invention proposes a predefined action recognition method based on human skeleton for human-computer interaction posture classification

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  • Human skeleton point parameter acquisition device applied to humanoid motion mimicry and recognition method thereof
  • Human skeleton point parameter acquisition device applied to humanoid motion mimicry and recognition method thereof
  • Human skeleton point parameter acquisition device applied to humanoid motion mimicry and recognition method thereof

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Embodiment Construction

[0009] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0010] The embodiment of the present invention figure 1 Recognition program initialization flow chart. At the beginning of the establishment of the system, it first collects every point within the field of view and forms a depth image representing the surrounding environment. The sensor generates a stream of depth images at a rate of 30 frames per second to reproduce the surrounding environment in real time. Secondly, Kinect evaluates the depth-of-field image at the pixel level to identify different parts of the human body, uses a segmentation strategy to distinguish the human body from the background environment, and obtains the depth-of-field image after kicking out the background of the tracking object. Finally, Kinect evaluates every possible pixel of the Exemplar output to determine joint points, and generates a skeletal system map based on ...

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Abstract

The invention discloses a human skeleton point parameter acquisition device applied to humanoid motion mimicry and a recognition method thereof. The method is characterized by acquiring a depth image, recognizing human joint points by using the depth image by an OpenNI bone recognition algorithm library, extracting spatial coordinates, and providing control data for a robot controller by means of filtering, spatial vector calculation, and leg posture recognition. In view of a problem that posture recognition is influenced by environment so as to be low in recognition accuracy and poor in real-time performance, a new action recognition method based on human skeleton predefining is provided for human-machine interaction posture classification. The method give full scope to an advantage that the Kinect can obtain a depth image feature, organically combines 2bitBP characteristics, constitutes a skeleton predefined posture type, performs posture classification by using an improved support vector machine, and is good in real-time performance, high in recognition accuracy, and good in robustness in the case of illumination variation. The recognition efficiency and accuracy can meet a natural human-machine interaction system requirement.

Description

technical field [0001] The invention relates to a human body bone point parameter acquisition system and a recognition method applied to human imitation motion mimicry, which classifies and recognizes human body movements to realize humanoid robot motion mimicry. Background technique [0002] As a non-cooperative human body tracking system, Kinect can provide skeletal images, depth of field images, and can perform skeleton tracking. Through the cooperation of the depth-of-field camera and the RGB camera, Kinect can put the 3D image of the object on the screen. These characteristics of Kinect make it a popular tool for body recognition. However, relying only on depth information, there are also some defects in the recognition process: when the clothing surface is rough, the image pixels jump seriously, and the depth image is unstable; when there is occlusion or other moving objects, it cannot be accurately recognized. Aiming at these problems, the present invention proposes ...

Claims

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Application Information

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IPC IPC(8): G06T7/285G06K9/62
CPCG06T2207/30196G06F18/2411
Inventor 黄根勇
Owner 江西制造职业技术学院
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