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A Texture-Free 3D Object Tracking Method Based on Confidence and Feature Fusion

A three-dimensional object and feature fusion technology, applied in the field of computer vision, can solve problems such as failure and inconsistent error measurement, and achieve the effect of improving stability

Active Publication Date: 2021-03-26
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Aiming at the deficiencies of the prior art, the present invention provides a textureless 3D object tracking method based on confidence and feature fusion. The tracking method solves the problem of single-type features in a specific scene on the basis of fusing color features and edge features. failure problem
[0010] The present invention calculates confidence degrees for edge points and area points respectively, automatically normalizes them, and calculates the weight of each energy item according to the confidence degrees, so as to solve the problem of inconsistency in error measurement of different features, and avoid the setting of additional hyperparameters at the same time; Confidence calculates the weight of each cluster, so as to set its weight to participate in optimization, and shield the negative impact of outliers

Method used

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  • A Texture-Free 3D Object Tracking Method Based on Confidence and Feature Fusion
  • A Texture-Free 3D Object Tracking Method Based on Confidence and Feature Fusion
  • A Texture-Free 3D Object Tracking Method Based on Confidence and Feature Fusion

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Embodiment 1

[0068] A texture-free three-dimensional object tracking method based on confidence and feature fusion, the tracking method comprising the following steps:

[0069] (1) Input the 3D model of the tracking object, each frame of image taken by the RGB monocular camera, and the pose of the first frame into the computer, and use the color histogram according to the color information of the foreground point, background point and uncertain area point respectively. The graph establishes the color model of the corresponding foreground area, the color model of the background area and the color model of the uncertain area;

[0070] The color histogram indicates the proportion of different colors in the whole area;

[0071] In step (1), the point x in the uncertain region satisfies the following conditions:

[0072] When the point x is in the foreground area, but P f b , P f Indicates the probability that point x belongs to the foreground, P b Indicates the probability that point x bel...

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Abstract

The invention relates to a texture-free three-dimensional object tracking method based on confidence coefficient and feature fusion. The tracking method comprises the following steps: (1) establishinga color model; (2) dividing the pixel points into contour points and region points by using a cluster structure; (3) determining the weight alpha i of the edge item, the weight beta i of the color item and the cluster weight omega i according to the confidence coefficient of the contour point and the confidence coefficient of the region point; (4) solving an optimal pose according to the total energy equation corresponding to all the clusters, and rendering the three-dimensional model of the object to obtain an object area on the current frame image; and (5) repeating the steps until the tracking is finished. According to the method, a clustering structure is used, contour points and regional points are re-unified into one energy function, and the problem of non-uniform sampling points issolved; the confidence coefficients of the edge points and the region points are calculated respectively, the edge points and the region points are normalized automatically, the weight of each energyitem is calculated according to the confidence coefficients, and the problem of non-uniform error measurement of different features is solved.

Description

technical field [0001] The invention relates to a textureless three-dimensional object tracking method based on confidence and feature fusion, which belongs to the field of computer vision. Background technique [0002] 3D object tracking can continuously obtain the spatial position relationship between 3D objects and cameras, which is an important task in computer vision. At present, 3D tracking already has a wide range of application scenarios, such as industrial manufacturing, medical diagnosis, entertainment games, robots and other fields. According to the different types of video data used, 3D object tracking can be roughly divided into two categories: 3D tracking based on RGB-D video data and 3D tracking based on RGB video data [Lepetit V, FuaP. Monocular model-based 3d tracking of rigid objects :A survey. Foundations and in Computer Graphics and Vision, 2005, 1(1):1-89.]. [0003] The method based on RGB-D data tracking can obtain 3D information in the scene throu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/20G06T15/00
CPCG06T7/20G06T15/00G06T2207/10016
Inventor 秦学英李佳宸钟凡宋修强
Owner SHANDONG UNIV
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