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Distributed dtw human behavior recognition method based on human behavior characteristics

A recognition method and distributed technology, applied in the information field, can solve the problem of insufficient recognition accuracy

Active Publication Date: 2019-04-02
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the recognition technology of human behavior has insufficient recognition accuracy and cannot meet the existing needs.

Method used

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  • Distributed dtw human behavior recognition method based on human behavior characteristics
  • Distributed dtw human behavior recognition method based on human behavior characteristics
  • Distributed dtw human behavior recognition method based on human behavior characteristics

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Embodiment Construction

[0067] The present invention is described in detail below in conjunction with accompanying drawing:

[0068] Such as figure 1 As shown, the distributed information consistency estimation method of human joint points based on interactive multi-model realizes distributed processing of data and distributed fusion of information by constructing a dynamic distributed RGBD sensor network, and there is no centralized information processing in the network With the fusion center, sensor nodes only exchange information with neighboring nodes, and through a limited number of consistency iterations, the estimation of the perceived target state in the network is consistent.

[0069] The sensor network realizes the transmission of information through wireless communication. Each sensor is connected to a local processor, which can be a microcomputer or an ARM development board. After the local processor processes the information, it exchanges network data with neighboring nodes through wir...

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Abstract

The invention discloses a distributed DTW human behavior recognition method based on human behavior characteristics. The distributed DTW human behavior recognition method based on human behavior characteristics comprises the following steps: obtaining the current frame human behavior characteristics and adding it to the human behavior characteristic time series Middle; use the dynamic time warping algorithm DTW to match the current observed human behavior feature sequence with the specific behavior sequence that has been learned in the database template, and calculate the best matching similarity based on the chi-square distance between the two; take the inverse of the similarity , the matching probability is obtained after normalization; the action pattern matching probability information of each sensor is exchanged with adjacent sensor data as consistency information, and after consistent iterative calculation, the recognition results of adjacent sensor nodes are finally consistent. The present invention realizes accurate human body specific behavior recognition.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a distributed DTW human behavior recognition method based on human behavior characteristics. Background technique [0002] Human behavior recognition based on multiple RGBD cameras has attracted extensive attention from researchers, and has been applied to human behavior detection in operating rooms, factory workshops, automobile assembly, indoor monitoring and other environments, effectively solving the problem of human occlusion and possible human- The robot collision problem has important application value. [0003] At present, human behavior perception based on multiple RGBD sensors is still in a centralized stage, requiring one or more data fusion centers to fuse 3D data and human skeleton joint point data, which requires high computing power and robustness for data fusion centers , weak resistance to network instability and low scalability. [0004] With the developm...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/23G06F18/22G06F18/2415
Inventor 刘国良田国会
Owner SHANDONG UNIV
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