Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A crowd counting method and system based on a spatial perception attention refinement framework

A crowd counting and attention technology, applied in the field of computer vision, can solve the problem of not being able to exhaust all the scenes, and achieve the effect of improving the density distribution

Pending Publication Date: 2019-04-02
拓元(广州)智慧科技有限公司
View PDF4 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, limited by hardware resources and computing resources, these methods cannot exhaust all scenes; most importantly, these methods completely ignore the perspective distortion caused by different camera viewpoints in different scenes when designing the network structure— —The huge difference in crowd scale brought about by perspective distortion and the pose deformation inside and outside the plane are the most fundamental challenges faced by crowd counting

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
  • A crowd counting method and system based on a spatial perception attention refinement framework
  • A crowd counting method and system based on a spatial perception attention refinement framework
  • A crowd counting method and system based on a spatial perception attention refinement framework

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The implementation of the present invention is described below through specific examples and in conjunction with the accompanying drawings, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific examples, and various modifications and changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention.

[0045] figure 1 It is a flow chart of the steps of the crowd counting method based on the space-aware attention refinement framework of the present invention. Such as figure 1 Shown, a kind of crowd counting method based on the attention refinement frame of space perception of the present invention, comprises the steps:

[0046] Step S1, using convolutional neural network to generate feat...

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 crowd counting method and system based on a spatial perception attention refinement framework. The method comprises the following steps: generating feature maps, initial crowd density maps and density grade information of all training images by utilizing a convolutional neural network; inputting the information into an iterative spatial perception refining module, carrying out dynamic localization on the crowd density map in a spatial perception mode by utilizing a spatial regression mapping network, generating a corrected local density map, and carrying out a dynamiclocalization updating strategy for next iteration by combining a long-short-term memory module; Encoding the density level information to generate a density level graph, integrating the local densitygraph with the density level graph to serve as local and global information of each round of iteration, and inputting the local and global information into a local refining network; the local refinement network adjusts the density distribution of the input area, performs reverse space regression mapping on the input area, and updates and generates a crowd density map in a residual error learningmode; and iteratively carrying out the training process for multiple times to obtain a refined crowd density map.

Description

technical field [0001] The present invention relates to the field of computer vision based on deep learning, in particular to a crowd counting method and system based on a space-aware attention refinement framework. Background technique [0002] The crowd counting problem aims to analyze the number and area density of crowds in a scene. In recent years, due to the brilliant performance of deep learning methods in the field of computer vision, under the joint promotion of data and algorithms, the problem of crowd counting has attracted more and more researchers' attention due to its wide application prospects and subject exploratory nature. [0003] Many methods in the early years were mostly based on the framework of pedestrian detection, and completed the task of crowd counting through the idea of ​​detection first and then counting. Such methods generally analyze the appearance and motion patterns of pedestrians or extract texture features of multiple unit areas of the ima...

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
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/53G06F18/214G06F18/241Y02T10/40
Inventor 林倞李冠彬刘凌波王青
Owner 拓元(广州)智慧科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products