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Dense crowd people number counting method and system based on deep convolutional neural network

A deep convolution, dense crowd technology, applied in the field of image processing, can solve the problems of complex design process and long calculation time, and achieve the effect of improving accuracy and robustness

Active Publication Date: 2017-06-13
SHANDONG UNIV
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Problems solved by technology

However, the design process of the feature extraction model is relatively complicated, and the calculation time is relatively long.

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  • Dense crowd people number counting method and system based on deep convolutional neural network
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  • Dense crowd people number counting method and system based on deep convolutional neural network

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[0036] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0037] It should be noted that the terminology used here is only for describing specific embodiments, and is not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0038] In view of the wide application of deep learning in the field of machine vision (tracking, detection, positioning, etc.) and the ...

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Abstract

The invention discloses a dense crowd people number counting method and system based on a deep convolutional neural network. The counting method comprises the following steps that: obtaining an original image which contains a dense crowd, dividing the obtained original image into a plurality of image blocks with the consistent size, and recording an original image label to which each image blocks belongs; utilizing the image block and the original image label to which each image block belongs to train the deep convolutional neural network; and utilizing the deep convolutional neural network which finishes training to calculate the people number in each image block, carrying out accumulation on the people numbers in all image blocks, and finally, obtaining all people numbers in the original image. By use of the method, crowd counting accuracy and robustness can be effectively improved.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a method and system for counting the number of people in a dense crowd based on a deep convolutional neural network. Background technique [0002] Dense Crowd Counting refers to counting the number of individual targets for dense crowds in videos or images. In recent years, crowd counting based on pattern recognition and machine learning has been widely researched and applied in the field of intelligent monitoring, such as: the monitoring of the flow of people in airports and stations and the distribution of crowds in large shopping malls. By monitoring the number of people in a certain place, real-time density information can be provided to the management agency to effectively control the flow of people, thereby preventing potential crises caused by excessive crowd density. However, dense crowd counting still faces great challenges due to problems such as occlusion a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06M11/00G06N3/04G06N3/08
CPCG06M11/00G06N3/08G06N3/045
Inventor 常发亮张友梅王梦迪
Owner SHANDONG UNIV
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