Method and apparatus for marking three-dimensional point cloud based on fusion voxel

A technology of three-dimensional point cloud and marking method, which is applied in the processing of 3D images, image data processing, instruments, etc., to achieve the effect of fine classification recognition and point cloud marking

Pending Publication Date: 2019-01-01
HUNAN VISUALTOURING INFORMATION TECH CO LTD
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Problems solved by technology

However, the traditional semantic labeling based on voxel convolutional neural network requires that all points in the voxel share the same sem

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  • Method and apparatus for marking three-dimensional point cloud based on fusion voxel
  • Method and apparatus for marking three-dimensional point cloud based on fusion voxel
  • Method and apparatus for marking three-dimensional point cloud based on fusion voxel

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Embodiment Construction

[0037] According to the research of the inventors, it is found that the existing global context information modeling of scene point clouds can usually be solved by using the representation ability of graphical models. For example, the more common way is to combine the classifier with the conditional random field ( Conditional Random Fields (CRF) to estimate semantic labels for each data point. However, the classification recognition stage of the classifier and the CRF optimization stage are usually operated independently as separate modules, and there is no interaction between them, which limits the information exchange between the modules.

[0038] Among them, for the classifier, the 3D voxel convolutional neural network is a better choice. The 3D voxel convolutional neural network is extended from the 2D convolutional neural network, and it has also achieved good performance in the task of 3D object classification and recognition. Compared with the point cloud-based deep neu...

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Abstract

Embodiments of the present invention provide a three-dimensional point cloud marking method and apparatus based on a fusion voxel. The method comprises the following steps: the data set of the three-dimensional point cloud is voxelized and voxel features in the voxels are extracted based on the processing results to form a first voxel feature matrix; the first voxel feature matrix is used as the input of the three-dimensional convolution neural network to calculate the multi-scale feature of the voxel, and the multi-scale feature is fused in series to obtain the second voxel feature matrix. The first voxel feature matrix is used as the input of the three-dimensional convolution neural network to calculate the multi-scale feature of the voxel. Based on the feature interpolation algorithm, the voxel features in the second voxel feature matrix are extended to the points in the three-dimensional point cloud data set to obtain the point cloud feature matrix. The feature matrix of point cloud is inputted into the multilayer perceptron to mark the attributes of three-dimensional point cloud. The invention can realize fine classification and recognition point by point, so as to further improve the performance of point cloud marking.

Description

technical field [0001] The present invention relates to the technical field of data labeling, in particular to a fused voxel-based three-dimensional point cloud labeling method and device. Background technique [0002] With the widespread application of 3D sensors (such as LiDAR, Microsoft Kinect, ASUS Xtion, etc.) in various fields (such as mobile robots, autonomous driving, remote sensing interpretation, virtual reality, augmented reality, and battlefield situational It is also growing significantly, and 3D point cloud marking, as an important means of processing 3D data, refers to identifying the category attributes of each point in the observed scene point cloud data, and assigning a unique category to each point Labels, such as buildings, roads, or cars. However, the traditional semantic labeling based on voxel convolutional neural network requires that all points in the voxel share the same semantic label, and requires regular data input, and the labeling results obta...

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Application Information

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IPC IPC(8): G06T15/00G06N3/04
CPCG06T15/00G06N3/045
Inventor 马燕新鲁敏涂兵郭裕兰雷印杰
Owner HUNAN VISUALTOURING INFORMATION TECH CO LTD
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