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Point cloud registration method based on tensor voting method

A technology of tensor voting and point cloud registration, which is applied in image data processing, instruments, calculations, etc., can solve the problems of large errors, low efficiency, and long time consumption, and achieve good robustness, ensure registration efficiency, and avoid The effect of getting stuck in local optima

Pending Publication Date: 2022-01-07
YANSHAN UNIV
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Problems solved by technology

[0009] The technical problem to be solved in the present invention is to provide a point cloud registration method based on the tensor voting method to solve the problems of low efficiency, long time consumption and large error in the existing research methods

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  • Point cloud registration method based on tensor voting method
  • Point cloud registration method based on tensor voting method
  • Point cloud registration method based on tensor voting method

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Embodiment Construction

[0052] Below in conjunction with accompanying drawing and embodiment the present invention is described in further detail:

[0053] Such as figure 1 As shown, a point cloud registration method based on the tensor voting method includes the following steps:

[0054] S1. Obtain two sets of point cloud data of the target object, one set as the original point cloud, and one set as the target point cloud.

[0055] The two sets of point clouds are obtained by the rigid transformation of the target object. The rigid transformation means that the shape of the target object does not change, and only the rotation transformation and translation occur in the Euclidean space. Rigid transformation ensures that the distance between points is constant and the angle between lines is constant. Point cloud data can be collected by a depth camera, or can be obtained by using other monocular imaging systems or binocular imaging systems. Common depth cameras include Kinect and TOF cameras.

[00...

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Abstract

The invention provides a point cloud registration method based on a tensor voting method, and belongs to the field of machine vision target posture recognition, and the method comprises the following steps: obtaining two groups of point cloud data of a target object; filtering noise of the two groups of point cloud data; performing tensor coding on the two groups of preprocessed point cloud data; performing tensor voting on the two groups of encoded point cloud data; carrying out SVD (Singular Value Decomposition) on the tensor matrix after voting; comparing the characteristic values obtained by processing the two groups of point clouds, creating a similarity function, and taking the group of points with the minimum value as a tensor registration result; and calculating a mathematical relationship between the two groups of point cloud feature matrixes to obtain a rotation matrix and a translation vector. The problems that an existing research method is low in efficiency, long in consumed time and large in error are solved.

Description

technical field [0001] The invention relates to the field of machine vision target gesture recognition, in particular to a point cloud registration method based on a tensor voting method. Background technique [0002] With the continuous development of machine vision technology and three-dimensional operation technology, researchers are now exploring a more advanced technology to make computers more in line with the way the human brain works. In the research of machine vision, registration is one of the important research topics. Registration technology has a wide range of applications, and every industry needs an efficient and accurate registration technology to replace people and liberate the labor force. [0003] In the field of machine vision, the registration of point sets adopts the automatic registration method, which uses a certain algorithm or statistical law to use a computer to calculate the misalignment between two point sets, so as to achieve the effect of auto...

Claims

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Application Information

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IPC IPC(8): G06T7/32G06T5/00
CPCG06T7/32G06T2207/10028G06T2207/20024G06T5/70
Inventor 林洪彬郭聃杨博关勃然魏佳宁陈泽宇
Owner YANSHAN UNIV
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