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Road congestion determination method, terminal device and computer readable storage medium

A road and congestion information technology, applied in the field of computer vision, can solve problems such as high requirements for external detection environment, inability to judge road congestion, and poor anti-interference ability.

Inactive Publication Date: 2018-09-18
何澜
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] The main purpose of the present invention is to provide a method for judging road congestion, terminal equipment and a computer-readable storage medium, aiming to solve the problem of poor anti-interference ability and high requirements for external detection environment in the prior art when monitoring road traffic conditions. Once the external environment deviates, it is impossible to accurately judge the technical problem of road congestion

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  • Road congestion determination method, terminal device and computer readable storage medium
  • Road congestion determination method, terminal device and computer readable storage medium
  • Road congestion determination method, terminal device and computer readable storage medium

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Embodiment Construction

[0044] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0045] The solution of the embodiment of the present invention is mainly: use the end-to-end deep learning code framework to judge the current road congestion in real time, mainly extract the target convolution feature of the road image to be processed through the preset neural network model, and convert the target The convolution features are respectively substituted into the classification decoder, the detection decoder and the segmentation decoder to obtain category results, position results and semantic segmentation results. The classification decoder is a decoder for classifying and recognizing the convolution features, and the detection decoder It is a decoder for positioning and detecting convolutional features, and the segmentation decoder is a decoder for semantically segmenting convolutional features. Accordi...

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Abstract

The invention discloses a road congestion determination method, a terminal device and a computer readable storage medium. Target convolution features of a to-be-processed road image is extracted by apreset neural network model; the target convolution features are substituted into a classification decoder, a detection decoder, and a segmentation decoder respectively to obtain a classification result, a position result, and a semantic segmentation result; according to the classification result, the position result, and the semantic segmentation result, a road surface area coordinate and a vehicle area coordinate in the to-be-processed road image are determined; road congestion information of the to-be-processed road image is determined based on the road surface area coordinate and the vehicle area coordinate. Therefore, the accuracy of the road congestion determination is improved; the processing time of the road congestion determination is shortened; the interference by the external environment is eliminated; and the road congestion can be determined reliably in real time.

Description

technical field [0001] The present invention relates to the field of computer vision, in particular to a method for judging road congestion, a terminal device and a computer-readable storage medium. Background technique [0002] With the rapid development of the national economy and the acceleration of urbanization, the number of motor vehicles and road traffic in my country has increased rapidly, and the problem of traffic congestion has become increasingly serious. In this case, it is particularly important to use an advanced traffic monitoring system to monitor road traffic conditions in real time, improve the response speed to emergencies such as road congestion, and achieve final traffic control and guidance. [0003] However, traffic control and guidance must be based on the acquisition of real-time and accurate traffic flow statistical information. The early manual statistical method not only consumes manpower, but also obtains real-time information that is difficult ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01G06K9/62G06K9/00
CPCG08G1/0133G06V20/52G06V2201/08G06F18/24
Inventor 何澜
Owner 何澜
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