Identity recognition method based on gait image

A technology of identity recognition and gait, applied in the field of identity recognition, can solve the problems of low recognition rate, long training time, poor robustness, etc., and achieve the effect of improving training and recognition efficiency, recognition rate and robustness

Active Publication Date: 2018-09-11
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

[0008] The identification based on gait images can solve some disadvantages of the current common identification methods, but the exis...

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  • Identity recognition method based on gait image
  • Identity recognition method based on gait image
  • Identity recognition method based on gait image

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Embodiment Construction

[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the implementation methods and accompanying drawings.

[0040] see figure 1, the identity recognition method based on the gait image of the present invention mainly comprises two stages, and one is that the training stage mainly trains and optimizes the feature learning network, and generates the identity recognition model for use in the recognition stage; the second is utilizing the feature learning network obtained in the training stage The model identifies the identity and uses the voting algorithm to statistically predict the results to identify the identity. The specific implementation process of each stage is as follows:

[0041] S1: The training stage mainly trains and optimizes the feature learning network, and generates an identity recognition model for use in the recognition stage...

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Abstract

The invention discloses an identity recognition method based on a gait image. The method includes: a training step: performing pedestrian detection and image preprocessing on a gait image sequence, assigning tag values to corresponding gait images, performing training by employing a characteristic learning network formed by a convolutional restricted Boltzmann machine and a full connection layer,and generating a characteristic learning network model with identity recognition and a characteristic central value model; and a recognition step: performing pedestrian detection and image preprocessing on a to-be-recognized gait image, calculating the gait periodicity through a normalized autocorrelation function to obtain a gait sequence of one period, and recognizing the identity of a pedestrian through a deep learning network and a voting algorithm. According to the method, the periodic gait image sequence is regarded as input, and complete gait information is reserved; characteristic learning is performed by employing the deep learning network, and more gait characteristics with a distinguishing degree are obtained to improve the recognition rate; and the recognition accuracy and robustness can be improved through combination usage of the deep learning network and the voting algorithm.

Description

technical field [0001] The invention relates to the technical field of identification, in particular to an identification method based on gait images. Background technique [0002] Public security is related to social stability, economic development and other major issues, and has long attracted people's attention. An important part of this is fast and accurate identity authentication for public safety. Therefore, related identification technologies have also emerged as the times require. [0003] At present, commonly used identification technologies based on biological characteristics include iris recognition, face recognition and fingerprint recognition. These identification technologies have brought great convenience and security to daily life, such as mobile payment, face attendance, etc. . Although these identification technologies have brought many conveniences to people, they are also easily affected by factors such as distance, image resolution, and illumination, ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/08
CPCG06N3/084G06V40/25G06V20/41G06F18/22
Inventor 刘欣刚余涛梅永勇王艺豪严敬仁代成汪卫彬
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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