Indoor human body posture recognition method based on weighted combined distance time frequency transformation

A technology that combines distance and human body posture, applied in the field of radar, can solve the problems of sensor network traffic expansion, large impact of video image environment, invasion of privacy, etc., and achieve strong anti-interference ability, high classification accuracy, and high distance resolution Effect

Active Publication Date: 2017-10-24
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

However, video image information will cause the expansion of sensor network traffic, and video image detection is greatly affected by the environment, and privacy is violated to a certain extent.
Wearable human gesture recognition devices also have two major disadvantages: data memory and applicability
Existing research mainly uses radar to extract Doppler information of some periodic human body postures, such as arm swing walking, continuous jumping, squatting and other actions, which have very large limitations

Method used

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  • Indoor human body posture recognition method based on weighted combined distance time frequency transformation
  • Indoor human body posture recognition method based on weighted combined distance time frequency transformation
  • Indoor human body posture recognition method based on weighted combined distance time frequency transformation

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Embodiment 1

[0115] An indoor human gesture recognition method based on weighted joint distance-time-frequency transformation, comprising the following steps:

[0116] Step 1. In image 3 In the scene diagram of the experiment, there are 6 actions measured in the experiment, (1) turning around, (2) bending over, (3) sitting, (4) squatting, (5) jumping and (6) falling. There are 4 subjects in the experiment, each action is performed 10 times, and finally 240 packets of data are obtained.

[0117] Step 2: Intercepting the data including the human posture after filtering for 4 seconds, and selecting effective range gates, the energy contained in these range gates accounts for 95% of the total energy of the signal.

[0118] Step 3. Obtain the weighting coefficient according to the energy size of each effective range gate, use the short-time Fourier transform STFT to obtain the time-frequency distribution diagram of each effective range gate, and then use the time-frequency distribution diagra...

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Abstract

The invention discloses an indoor human body posture recognition method based on weighted combined distance time frequency transformation, and the method comprises the steps: firstly carrying out the MTI filtering of indoor human body posture data recorded by a UWB (ultra wide band) radar, extracting the data comprising the body posture, and selecting an effective distance gate; secondly obtaining a combined distance time frequency distribution map through the weighted combined distance time frequency transformation, and extracting the feature parameters of a body envelope in the map; thirdly determining the mapping relation between different postures and the feature parameters through a machine learning algorithm; finally determining the class of body posture according to the obtained mapping relation. The method is effective and feasible, is reliable in performance, and can accurately recognize different indoor body postures.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to an indoor human body posture and recognition method based on ultra-wideband radar. Background technique [0002] Human pose recognition is one of the challenging research hotspots in recent years. It has broad application prospects in the fields of security monitoring, human-computer interaction and medical care. In addition, as my country's population aging phenomenon is becoming more and more serious, the proportion of the elderly in the entire population is gradually increasing, and the social pressure faced by children is also increasing. How to effectively carry out early warning and effective monitoring of the safety problems faced by the elderly indoors at home is a major problem facing the whole society. With the development of computer technology, the monitoring system based on human body posture recognition can provide effective early warning and notify family members b...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/08G01C21/20G06K9/62
CPCG01C21/206G01S13/08G06F18/2411
Inventor 顾陈廖志成洪弘李彧晟孙理朱晓华丁传威邹宇
Owner NANJING UNIV OF SCI & TECH
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