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A human identification method based on sequential depth images

A depth image and identity recognition technology, which is applied in the field of human identity recognition based on sequence depth images, can solve problems such as poor robustness and limited accuracy rate in application scenarios, so as to improve the recognition rate, improve the effect of human identity recognition, reduce the The effect of small amount of calculation

Active Publication Date: 2020-09-08
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0010] In view of the above defects or improvement needs of the prior art, the present invention provides a human body identification method based on sequence depth images, thereby solving the technical problems of poor robustness and limited accuracy in the application scenarios of the prior art

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  • A human identification method based on sequential depth images
  • A human identification method based on sequential depth images
  • A human identification method based on sequential depth images

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Embodiment Construction

[0052] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0053] Such as figure 1 As shown, a human body identification method based on sequence depth images, including:

[0054] (1) collecting sequence depth images of the human body, the sequence depth images comprising the gait motion of the human body;

[0055] (2) The use of convolutional neural network and recursive neural network to perform human body joint point regression based on each frame ...

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Abstract

The invention discloses a human body identification method based on a sequence depth image, comprising: collecting the sequence depth image of a human body, and using a convolutional neural network and a recursive neural network to perform regression of human body joint points based on the sequence depth image to obtain the coordinate positions of the human body joint points ; Use the coordinates of the joint points of the human body to calculate the body posture feature vector, use the static feature classifier to identify, and obtain the human body identity recognition score of the static feature; extract the human body motion behavior feature from the sequence depth image, and use the dynamic feature classifier to perform Recognition to obtain the human body recognition score of dynamic features; the weighted calculation of the static and dynamic features of the human body recognition score to obtain the human body recognition score, and then obtain the human body recognition result. The present invention has strong robustness, and the accuracy rate is not affected by application scenarios.

Description

technical field [0001] The invention belongs to the cross technical field of digital image processing and machine learning, and more specifically relates to a human body identification method based on sequence depth images. Background technique [0002] With the rapid development of information technology, the digitization of personally identifiable information is becoming more and more common. In the fields of security, finance, criminal investigation, and elderly care, the demand for human identification technology is becoming more and more urgent. Due to the shortcomings of not easy to carry, easy to lose, easy to damage, and low security, traditional identification technology is gradually replaced by identity authentication technology based on biometrics. The research on voiceprint, fingerprint, iris recognition and other technologies has become more and more mature, and has greatly improved in terms of security, confidentiality, and portability. However, most of these...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06K9/66G06N3/04
CPCG06V40/25G06V30/194G06N3/045G06F18/241G06F18/24147
Inventor 肖阳张博深曹治国毛靖朱子豪王焱乘
Owner HUAZHONG UNIV OF SCI & TECH
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