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

Small group real-time detection method of intermediate-density scene

A real-time detection and small group technology, applied in image data processing, instruments, character and pattern recognition, etc., to achieve the effect of fast operation speed, high precision and recall rate, and real-time operation

Active Publication Date: 2017-08-04
SHANGHAI UNIVERSITY OF ELECTRIC POWER
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Realize rapid real-time detection and overcome the problems existing in traditional research

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
  • Small group real-time detection method of intermediate-density scene
  • Small group real-time detection method of intermediate-density scene
  • Small group real-time detection method of intermediate-density scene

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] The specific steps of the real-time detection method for small groups in medium-density scenes are as follows:

[0019] 1. Input video and individual movement track detection data; according to the individual movement track data, the detection coordinate position and movement speed of each individual in each frame can be obtained.

[0020] 2. Establish a target prediction model for each moving individual and calculate the target direction of each moving individual:

[0021] Such as figure 1 A schematic diagram of the target prediction model of the present invention is shown. The origin in the figure represents pedestrians, and the dotted line behind them represents their trajectory. Black solid thick lines simulate obstacles. As can be seen from the figure, the target of pedestrian A is behind the obstacle, and the direction of the target is marked with a dotted arrow. Therefore, A produces an avoiding force to avoid obstacles in the opposite direction, and at the s...

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 relates to a small group real-time detection method of an intermediate-density scene. The method includes: inputting a video and individual movement track detection data; obtaining a detection coordinate position and a motion speed of each individual in each frame according to the individual movement track data; establishing a target prediction model for each motion individual; calculating a target direction [eta]i of each motion individual; and substituting [eta]i into a correlation filtering algorithm for small group detection to obtain a correlation small group. The method is applicable to various types of intermediate-density dense scenes, the operation speed is fast, real-time operation can be realized, the accuracy and the recall rate in various scenes are high, and the method is an online algorithm so that offline learning is avoided.

Description

technical field [0001] The invention relates to a small group detection technology, in particular to a real-time detection method for a small group in a medium-density scene. Background technique [0002] Dense scene analysis is a research hotspot in the field of computer vision and an important and challenging topic in intelligent video surveillance research. Intensive scenes can be seen everywhere in daily life, such as public gatherings, large supermarkets, shopping malls, public transportation stations, etc. With the development of society, the increase of population and the aggravation of environmental congestion, capturing the dynamic characteristics of dense groups and mining group movement information is not only of scientific research value, but also of great significance to social public security. [0003] Traditional research on dense scenes usually only takes moving individuals as objects for detection, tracking and behavior analysis. In recent years, studies h...

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): G06K9/00G06T7/269
CPCG06T2207/30241G06T2207/30196G06V20/53
Inventor 邵洁
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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

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