Human behavior recognition method and human behavior recognition system based on depth neural network

A deep neural network and recognition method technology, applied in neural learning methods, biological neural network models, character and pattern recognition, etc. The effect of recognition speed, improving accuracy and protecting user privacy

Inactive Publication Date: 2015-08-19
SHENZHEN UNIV
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Problems solved by technology

[0005] In view of this, the purpose of the embodiments of the present invention is to provide a human behavior recognition method and recognition system based on a deep neural network, which aims to solve the problems of limited types of human behavior recognition, low recognition accuracy, and slow recognition speed in the prior art. question

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  • Human behavior recognition method and human behavior recognition system based on depth neural network
  • Human behavior recognition method and human behavior recognition system based on depth neural network
  • Human behavior recognition method and human behavior recognition system based on depth neural network

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Embodiment Construction

[0045] 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. A human behavior recognition method and recognition system based on deep neural network

[0046] The specific embodiment of the present invention provides a kind of human behavior recognition method based on deep neural network, mainly comprises the following steps:

[0047] S11. Obtain the original depth data stream of the actor;

[0048] S12. Extract the skeleton joint point data of the human body through the original depth data stream of the actor;

[0049] S13. Using the extracted three-dimensional coordinates corresponding to the joint point data of the human body skeleton to model the entire ...

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Abstract

The invention provides a human behavior recognition method based on a depth neural network, comprising the following steps: acquiring original depth data stream of an actor; extracting human skeleton joint data from the original depth data stream of the actor; modeling the entire human body with three-dimensional coordinates corresponding to the extracted human skeleton joint data; extracting features by modeling the entire human body, sending feature data to a restricted Boltzmann machine network for preprocessing, training out a depth neural network model based on received weight initialization BP neural network parameters, and identifying a behavior from a feature extraction result; overlapping the extracted human skeleton joint data and the actual human body through multi-threaded parallel processing, and displaying the identified behavior in real time; and establishing an abnormal behavior template library and alarming for a detected abnormal behavior. The change of human behavior can be detected in real time, and alarm can be raised for abnormal behaviors (such as fall) of a human body.

Description

technical field [0001] The invention relates to the field of video recognition, in particular to a human behavior recognition method and recognition system based on a deep neural network. Background technique [0002] As we all know, now is the era of aging of the human body. my country has the largest elderly population in the world. According to reports, the elderly population will reach 248 million by 2020. Coupled with the implementation of family planning, the only child is busy with work. Lives independently most of the time. Many abnormal behaviors cannot be detected in time, so that the tragedies of the elderly delaying treatment and losing their lives occur from time to time, seriously affecting the quality of life of the elderly. For example, falling behavior is the direct cause of injury death among the elderly over 65 years old in my country. If we can accompany the empty-nest elderly in their daily life, effectively identify their behavior, and detect abnormal ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/08G06V40/103
Inventor 陈亮龙伟王娜李霞
Owner SHENZHEN UNIV
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