A Gait Recognition Method Robust to Changes in Walking State

A gait recognition and state change technology, applied in the field of pattern recognition and machine learning, can solve the problems of complex matching process, high modeling complexity, and short model method features

Inactive Publication Date: 2016-04-06
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

The model method is less affected by external interference, has short features, and can describe the changes of various parts of the body. When the modeling is accurate, the recognition effect is good, but the modeling is complicated and the matching process is complicated.

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  • A Gait Recognition Method Robust to Changes in Walking State
  • A Gait Recognition Method Robust to Changes in Walking State
  • A Gait Recognition Method Robust to Changes in Walking State

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Embodiment Construction

[0087] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0088] The database of the experiment is CASIA(B) gait database, which contains 3 kinds of walking states, which are normal gait (denoted as 'nm'), gait with backpack (denoted as 'bg') and coat change Gait (denoted as 'cl'). Take the gait recognition from the side view as an example to illustrate the experimental effect of the method provided by this patent. For each gait video image, the gait energy image (GEI) is used to express the gait characteristics, and the GEI are 64×64 pixels in size. Such as image 3 shown.

[0089] Four groups of gait recognition experiments that are robust to changes in walking state:

[0090] (1) The registration set consists of each person's first normal gait; the training set consists of each person's first normal gait and the first gait with a backpack; the test set consists of each person's second gait with a backpa...

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Abstract

The invention discloses a gait recognition method that is robust to changes in walking states, establishes distance measurement expressions between gait feature matrices in different walking states, and uses machine learning methods to integrate different The samples of the walking state are connected and coupled into the same image space. After the training is completed, the respective projection matrices of the samples of different walking states can be obtained; The projection axes of different walking states are projected separately, and the nearest neighbor classifier is used for classification. The present invention does not need to predict and estimate from one walking state to another walking state, and can directly use machine learning to solve the problem of gait recognition in walking state changes.

Description

technical field [0001] The invention belongs to the fields of pattern recognition and machine learning, in particular to a gait recognition method robust to changes in walking states. Background technique [0002] The tragic event of "9.11" has caused the whole world to pay special attention to the enhancement of national defense, the security of terrorist attacks, and the automatic protection capabilities after terrorist attacks. Biometric identification technology has been successfully applied in identity verification, access control systems, and may also be applied in the identification of terrorists in airports and other security-sensitive places. The HID (humanidentificationatadistance) research project funded by the US Defense Advanced Research Projects Agency in 2000 is to develop and improve the performance of the current large-scale identification system under long-distance, so as to have high reliability and robust identification capabilities. In 2003, the Interna...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/66
Inventor 贲晛烨江铭炎张鹏徐昆陆华李斐潘婷婷
Owner SHANDONG UNIV
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