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Luggage volume automatic classification method based on generative query network

A technology for automatic classification and luggage, applied in biological neural network models, neural learning methods, instruments, etc., can solve problems such as inconvenient luggage check-in, limited check-in personnel, missing luggage inspection, etc.

Active Publication Date: 2019-06-07
SUZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the large number of passengers checking in luggage and the limited number of check-in personnel, the method of visually measuring the size of luggage may easily cause some oversized luggage to be missed, which brings inconvenience to luggage checking. Inefficient checks and extended baggage check-in times

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  • Luggage volume automatic classification method based on generative query network
  • Luggage volume automatic classification method based on generative query network
  • Luggage volume automatic classification method based on generative query network

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Embodiment Construction

[0043] Below in conjunction with principle of the present invention, accompanying drawing and embodiment the present invention is further described

[0044] see Figure 1 to Figure 4 , as shown in the legend, an automatic luggage volume classification method based on the generated query network, including the following steps:

[0045] (1) Provide a scene image acquisition subsystem, a three-dimensional model generation subsystem, a scene segmentation subsystem, a baggage volume calculation subsystem and a baggage classification subsystem, the above-mentioned scene image acquisition subsystem includes a camera, and the above-mentioned three-dimensional model generation subsystem The system includes generating a query network, the above-mentioned scene segmentation subsystem includes a point cloud library, and the above-mentioned camera is a monocular camera;

[0046] (2) Use the above camera to collect pictures of the current actual scene including luggage to form a picture se...

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Abstract

The invention discloses a luggage volume automatic classification method based on a generative query network. The method comprises the following steps: (1) providing a scene image acquisition subsystem comprising a camera, a three-dimensional model generation subsystem comprising the generative query network, a scene segmentation subsystem and a luggage classification subsystem; (2) carrying out picture acquisition on the current actual scene containing the luggage through a camera; (3) taking the picture sequence obtained in the step (2) as input for generating a query network; (4) convertingthe three-dimensional model obtained in the step (3) into a point cloud file through a scene segmentation subsystem, and segmenting the point cloud file; and (5) calculating the volume of each pieceof luggage through a luggage classification subsystem according to the obtained point cloud data of each piece of luggage, and identifying each piece of luggage as a volume range where the volume of each piece of luggage is located. Due to the adoption of an artificial intelligence method, subsidy positioning and volume estimation can be realized without excessive manual intervention, and the method has wider applicability.

Description

technical field [0001] The invention relates to the field of artificial intelligence and control technology, in particular to an automatic luggage volume classification method based on a generated query network. Background technique [0002] When boarding the plane, you need to go through baggage check-in procedures. Since general airlines have issued corresponding restrictions on the weight and volume of checked luggage, the check-in personnel need to weigh the luggage and visually measure the size of the luggage when checking in the luggage. Ensure that the baggage meets the specified weight and volume requirements for checked baggage. Due to the large number of passengers checking in luggage and the limited number of check-in personnel, the method of visually measuring the size of luggage may easily cause some oversized luggage to be missed, which brings inconvenience to luggage checking. Checking is inefficient and lengthens the time it takes to check in bags. Content...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCY02D10/00
Inventor 朱斐徐大勇刘全
Owner SUZHOU UNIV
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