Crowd counting method and device, electronic equipment and computer storage medium

A crowd counting, deep neural network technology, applied in computer parts, computing, neural learning methods, etc., can solve problems such as low accuracy, and achieve the effect of improving accuracy

Pending Publication Date: 2021-01-15
ZHEJIANG UTRY INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application provides a crowd counting method, device, electronic equipment, and computer storage medium to at least solve the problem of low accuracy in crowd counting of images with dense crowd targets and small sizes based on convolutional neural networks in the related art

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  • Crowd counting method and device, electronic equipment and computer storage medium
  • Crowd counting method and device, electronic equipment and computer storage medium
  • Crowd counting method and device, electronic equipment and computer storage medium

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Embodiment Construction

[0044] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0045]Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present application, and those skilled in the art can also apply the present application to other similar scenarios. In addition, it can also be understood that although such development efforts may be complex and lengthy, for those of o...

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Abstract

The invention relates to a crowd counting method and device, equipment and a medium, and the method comprises the steps of calculating a training image by a convolutional neural network to obtain a first feature, and calculating the first feature through a first-order statistical attention network to obtain a second feature, calculating the first feature by a second-order counting attention network to obtain a third feature, wherein the third feature represents the head feature of a crowd target with a small size in the training image, and calculating the first feature, the second feature andthe third feature by a cascade layer to obtain a prediction density map; and training a second-order hybrid deep neural network according to the prediction density map and a label density map, calculating a to-be-counted image by the trained second-order hybrid deep neural network to obtain a crowd density map, and calculating the number of people in the to-be-counted image according to the crowddensity map. Through the crowd counting method and device, the problem of low accuracy in crowd counting of images with dense crowd targets and small sizes based on the convolutional neural network issolved.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a crowd counting method, device, electronic equipment and computer storage medium. Background technique [0002] Crowd counting aims to count the number of people in an image and plays a vital role in practical applications such as video surveillance, traffic planning, and public safety. In related technologies, due to the extremely uneven distribution of crowd density in the image, the counting method based on Deep Learning (DL) uses a multi-array Convolutional Neural Network (CNN) to extract different scales. The head features of the crowd target are used to predict the crowd density map, and then the number of people in the image can be counted. However, in a scene where a large number of people gather, there will be a situation where the size of the crowd target is small, and the head features extracted by the convolutional neural network cannot accurately represent ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/53G06N3/045G06F18/2411
Inventor 嵇望丁大为江志勇王哲
Owner ZHEJIANG UTRY INFORMATION TECH CO LTD
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