Gait identifying method with robustness to walking gait changes

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

Inactive Publication Date: 2013-08-28
SHANDONG UNIV
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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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  • Gait identifying method with robustness to walking gait changes
  • Gait identifying method with robustness to walking gait changes
  • Gait identifying method with robustness to walking gait changes

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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'). Taking the gait recognition from the side view as an example to illustrate the experimental effect of the method provided by this patent, each gait video image is expressed in the form of a gait energy image (GEI). And the size of the GEI is 64×64 pixels. 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 backpack gait compositi...

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Abstract

The invention discloses a gait identifying method with robustness to walking gait changes. A distance metric expression among gait feature matrixes of different walking states is established, samples of different walking states of a same individual in a training stage are related and are coupled into a same image space through a machine learning strategy, and after training is completed, projection matrixes of the samples themselves under the different walking states can be obtained. In an identifying stage, when the walking states of the samples to be tested are not uniform with walking states of a registered sample collecting base, projection on projection shafts of the different walking states obtained through training are respectively conducted, and classification is conducted by the adoption of a nearest neighbor classifier. By means of the gait identifying method, prediction and estimation can be conducted without the need of changing one walking state to another walking state, and the gait identifying problem of the walking gait changes can be solved by the direct adoption of the machine learning.

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 (human identification at a distance) research project funded by the U.S. Defense Advanced Research Projects Agency in 2000 is to develop and improve the performance of the current large-scale identification system under long-distance, with high reliability and robust identification. ability. In 2003, the International...

Claims

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Application Information

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Patent Type & Authority Applications(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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