Distributed DTW (Dynamic Time Warping) human behaviour intention identification method based on human behaviour characteristics

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

Active Publication Date: 2016-11-16
SHANDONG UNIV
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Problems solved by technology

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

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  • Distributed DTW (Dynamic Time Warping) human behaviour intention identification method based on human behaviour characteristics
  • Distributed DTW (Dynamic Time Warping) human behaviour intention identification method based on human behaviour characteristics
  • Distributed DTW (Dynamic Time Warping) human behaviour intention identification method based on human behaviour 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 (Dynamic Time Warping) human behaviour intention identification method based on human behaviour characteristics. The distributed DTW human behaviour intention identification method based on the human behaviour characteristics comprises the following steps of: obtaining human behaviour characteristics in a current frame, and adding the human behaviour characteristics in the current frame into a human behaviour characteristic time sequence; matching a currently observed human behaviour characteristic sequence with a learned specific behaviour sequence in a database template by utilizing a DTW algorithm, and calculating the best matching similarity of the two based on a chi-square distance; reversing the similarity, and performing normalization to obtain a matching probability; and, taking an action mode probability value of each sensor as consistency information amount, performing data exchange with an adjacent sensor again, and performing consistency iterative operation, so that identification results of adjacent sensor nodes are same finally. By means of the distributed DTW human behaviour intention identification method based on the human behaviour characteristics disclosed by the invention, precise human specific behaviour identification can be realized.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a distributed DTW human behavior intention 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 th...

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Application Information

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Patent Type & Authority Applications(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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