Method and system for counting people in dense crowds 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: 2019-04-30
SHANDONG UNIV
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and system for counting people in dense crowds based on deep convolutional neural network
  • Method and system for counting people in dense crowds based on deep convolutional neural network
  • Method and system for counting people in dense crowds based on deep convolutional neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[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 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method and system for counting the number of people in a dense crowd based on a deep convolutional neural network. Wherein, the counting method includes acquiring an original image containing dense crowds, dividing the acquired original image into several image blocks of the same size and recording the original image label to which each image block belongs; The original image labels to train the deep convolutional network; use the trained deep convolutional network to calculate the number of people in each image block, and accumulate the number of people in all image blocks, and finally get all the people in the original image. The invention effectively improves the accuracy and robustness of crowd counting.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap