Human body posture real-time estimation method based on RGB-D image feature fusion

A technology of human posture and image features, applied in image analysis, image data processing, biometric recognition and other directions, can solve the problems of poor robustness, easy to be affected by illumination changes, misrecognition of hand-held tools, etc., to improve robustness, The effect of reducing misidentification and reducing uncertainty

Pending Publication Date: 2020-12-25
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the disadvantages of misrecognition of hand-held tools in the human body pose estimation method based on depth images and the human body pose estimation method based on color images is easily affected by illumination changes and has poor robustness, the present invention provides a hu...

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  • Human body posture real-time estimation method based on RGB-D image feature fusion
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  • Human body posture real-time estimation method based on RGB-D image feature fusion

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Embodiment Construction

[0024]The present invention will be further described below in conjunction with the drawings.

[0025]Referencefigure 1 ,figure 2 withimage 3 , A real-time estimation method of human pose based on RGB-D image feature fusion, the method includes the following steps:

[0026]Step 1) Obtain a sample of human body posture information as a training set, and build a neural network model to sample the position y of the human joint point i at time t-1i,t-1 As the input of the network, the position y of the human joint point i at time ti,t As the expected output of the network, the neural network is trained to obtain the function f of the kinematics model of each joint pointi(·);

[0027]Step 2) Establish a kinematic model of each joint point of the human body in the depth vision sensor coordinate system, and determine the process noise wi,k-1 Covariance Qi,k , And establish a human body posture measurement model based on color images and depth images to determine the measurement noise respectivelywi...

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Abstract

The invention discloses a human body posture real-time estimation method based on RGBD image feature fusion. According to the method, a method based on event triggering is adopted to obtain human bodyposture fusion estimation of depth and color images. According to the invention, through fusion of color and depth image features, error identification of a hand-held tool is effectively reduced, andthe robustness of illumination change is improved; and in order to solve the problem that human body joint point motion modeling is difficult, a BP neural network is used for carrying out human bodyjoint point motion modeling, so that the uncertainty of each joint point motion model is reduced, and the accuracy and robustness of human body posture estimation are effectively improved.

Description

Technical field[0001]The invention belongs to the field of human body posture estimation, in particular to a real-time estimation method of human body posture based on RGB-D image feature fusion.Background technique[0002]Human body pose estimation has a wide range of applications in human-computer interaction, video surveillance, assisted driving, medical motion analysis, games and sports, etc., especially in the field of human-computer interaction. Human body pose estimation is the basis for recognition of human action and behavior. It can recognize human behaviors, and complete action imitation or make response actions play a vital role.[0003]In recent years, with the rise of deep learning, the research and development of human pose estimation technology based on color images has shifted from traditional target tracking methods to target tracking methods based on deep learning. The use of convolutional neural network (CNN) method can effectively extract 2D human pose information f...

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/08G06T7/277G06T7/55
CPCG06N3/084G06T7/277G06T7/55G06V40/20G06V40/10G06V10/56G06F18/253
Inventor 杨旭升王茜姿贾晓凌张文安
Owner ZHEJIANG UNIV OF TECH
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