Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Method and system for judging crowd density in image

A crowd density and image technology, applied in the field of image processing, can solve problems such as high computational complexity and difficult implementation, and achieve the effect of improving prediction accuracy and reducing redundant classifiers

Active Publication Date: 2013-05-29
北京汉王智远科技有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method seems simple, but its computational complexity is relatively high, and it is difficult to implement. It is only suitable for small problems.

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 judging crowd density in image
  • Method and system for judging crowd density in image
  • Method and system for judging crowd density in image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] In order to make the purpose, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] The basic scheme of the present invention is: based on the perspective model, divide the video image sample and the target video image area into image blocks, determine the combination form of the two classifiers, analyze and select the confidence training samples and train each two classifiers respectively, and use channel transmission The model gets the density level that maximizes the posterior probability.

[0042] The present invention provides an embodiment. refer to figure 1 , shows a flowchart of a method for estimating crowd density in a video image according to an embodiment of the present invention, which may specifically include the following steps.

[0043] Step 1: The block analysis unit selects a target area in t...

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 provides a method and system for judging the crowd density in an image. The method comprises the following steps: 1. selecting a target region from a video image sample acquired in an image acquisition device by utilizing a block analysis unit, and carrying out block analysis of image blocks in the target region; 2. determining the composite form of two-classifiers by a coding unit;3. selecting a confidence training sample by a training unit, and respectively training each two-classifier; and 4. obtaining the crowd density grade category of the maximum posteriori probability through a decoding unit by means of a channel transmission model. The method can be suitable for obtaining the credible crowd density grade in different scenes and can provide the basis for crowd monitoring and safety guarantee of important regions.

Description

technical field [0001] The invention belongs to the field of image processing and relates to a method for judging crowd density in an image. Background technique [0002] Traditional crowd monitoring is realized by monitoring a certain scene through closed-circuit television, which requires users to make judgments on the scene images. This method is highly subjective and cannot be used for quantitative analysis. The development of modern digital image processing technology provides a way to solve the above problems. Applying technologies such as image processing, pattern recognition, and computer vision to crowd monitoring can achieve automatic, objective, and real-time analysis of crowds. [0003] The crowd density judgment in the image is based on computer vision and pattern recognition technology, and the quantitative level of the crowd density in the image is obtained by analyzing and calculating the surveillance image or video. Crowd density information is a powerful...

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): G06T7/00G06K9/62
Inventor 黄磊刘昌平麻文华
Owner 北京汉王智远科技有限公司
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
Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com