Joint data association method based on multi-features of color image and depth image

A depth image and color image technology, applied in the information field, can solve problems such as no occurrence, and achieve the effect of expanding the perception range, improving robustness, and easy expansion

Active Publication Date: 2019-03-08
SHANDONG UNIV
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  • Abstract
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Problems solved by technology

[0005] Among them, related technologies on the joint data association based on multi-features of color images and depth images have not yet appeared.

Method used

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  • Joint data association method based on multi-features of color image and depth image
  • Joint data association method based on multi-features of color image and depth image
  • Joint data association method based on multi-features of color image and depth image

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Experimental program
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Embodiment Construction

[0038] The present invention is described in detail below in conjunction with accompanying drawing:

[0039] Such as image 3 As shown, the joint data association method based on multi-features of color images and depth images, which is aimed at multi-target tracking, includes:

[0040] System parameter initialization;

[0041] Multi-model interaction;

[0042] JPDA based on linear information filter and JPDA based on central difference information filter;

[0043] Send local information to neighboring sensor nodes;

[0044] Receive information from nearby sensor nodes;

[0045] Data association based on Mahalanobis distance;

[0046] The distributed information consensus algorithm realizes the fusion of multi-model results.

[0047] When estimating the consistency of distributed information, the details are:

[0048] By constructing a dynamic distributed RGBD sensor network, the distributed processing of data and the distributed fusion of information are realized. Ther...

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Abstract

The invention discloses a joint data association method based on multi-features of color images and depth images, and adopts joint data probability association algorithm local sensor nodes to perform the first data association between tracking targets and target observations; the realization of the Hungarian algorithm based on Mahalanobis distance The second data association between the sensor nodes for the tracking target; in the first data association, based on the multi-feature target observation candidate set adjustment mechanism, using the joint point position observation information z and the color image gradient direction histogram feature h c and depth image gradient orientation histogram feature h d Construct three threshold thresholds (γ z ,γ c ,γ d ) to limit the observation set size. The invention can improve the estimation precision and execution efficiency of the JPDA algorithm.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a joint data association method based on multi-features of color images and depth images. 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] When there are multi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06V40/20
Inventor 刘国良田国会
Owner SHANDONG UNIV
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