Cargo volume measurement method based on deep learning and three-dimensional reconstruction

A deep learning and three-dimensional reconstruction technology, applied in measurement devices, biological neural network models, image data processing, etc., can solve the problems of low measurement accuracy, complex algorithms, and high measurement environment requirements, and achieves the goal of reducing algorithm complexity, The effect of improving measurement accuracy and speeding up measurement efficiency

Active Publication Date: 2019-04-19
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0005] However, these technologies have their advantages and disadvantages when used. The raster image method has higher measurement accuracy, but it has higher requirements for the measurement envir...

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  • Cargo volume measurement method based on deep learning and three-dimensional reconstruction
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  • Cargo volume measurement method based on deep learning and three-dimensional reconstruction

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Embodiment Construction

[0022] The object volume measurement method based on deep learning and three-dimensional reconstruction proposed by the present invention will be explained in detail below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention.

[0023] The object volume detection method of the present invention includes the following parts: RGBD data acquisition, RGB data preprocessing, point cloud generation, point cloud splicing, point cloud segmentation, convex hull generation and volume detection, and its system structure is as follows: figure 1 shown.

[0024] The RGBD data acquisition part is responsible for collecting the RGBD data of the goods using two RGBD cameras. The RGBD cameras are installed in such as figure 2 As shown, 1 and 2 are two RGBD cameras, 3 is the target goods to be measured, the coordinate axis O-XYZ represents the space coordinate system of the three, and the coordinate axis o-xyz represents the ...

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Abstract

The invention relates to a cargo volume measurement method based on deep learning and three-dimensional reconstruction. The method comprises the steps of RGBD data acquisition, RGB data preprocessing,point cloud generation, point cloud splicing, point cloud segmentation, convex hull generation and volume detection, wherein the RGB data preprocessing adopts a deep learning method, and the deep learning method can accurately identify and segment a target object from a three-dimensional scene, so that the volume measurement precision of the target object is improved. Meanwhile, when the volume of a cargo is measured, a convex hull is used for replacing target point cloud data triangularization, the problems that the volume of an unsealed three-dimensional model cannot be measured and the measurement error of the actual space occupied by a concave cargo is large can be solved, and therefore practicability is further improved.

Description

technical field [0001] The invention relates to a cargo volume measurement method based on deep learning and three-dimensional reconstruction, and belongs to the technical field of logistics feature recognition and detection. Background technique [0002] With the progress of society and the development of science and technology, people's travel has gradually become more convenient and frequent. As the mainstream choice for people's long-distance travel, railway and aviation bear an increasing number of passengers. Therefore, the security inspection and consignment work of passenger luggage needs a lot of manpower, and at the same time, it shows its limitation and lag. Baggage identification and volume detection technology emerged as the times require. [0003] Due to the irregularity of the luggage shape and the complexity of the detection environment, the volume detection is difficult and the accuracy is low. The current methods of object volume measurement are roughly ...

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Application Information

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IPC IPC(8): G01B21/00G06T19/20G06N3/04
CPCG06T19/20G01B21/00G06N3/044G06N3/045
Inventor 王华锋张亚明王琦张鹏杜涛刘万泉
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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