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

Moving object detection method based on expansion mixed gauss model

A mixed Gaussian model and moving target technology, applied in the field of pattern recognition, can solve the problems of poor results and improve the detection effect

Inactive Publication Date: 2009-07-01
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF0 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This structure makes the output of "background modeling" directly determine the result of "shadow removal". If the result of "background modeling" is not good, then the result of "shadow removal" will definitely be worse

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
  • Moving object detection method based on expansion mixed gauss model
  • Moving object detection method based on expansion mixed gauss model
  • Moving object detection method based on expansion mixed gauss model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] Various details involved in the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be pointed out that the described embodiments are only intended to facilitate the understanding of the present invention, rather than limiting it in any way.

[0036] Moving target detection plays an important role in the follow-up links in monitoring, such as tracking and recognition. Based on the extended mixed Gaussian model, the invention implements a moving target detection method, which can effectively deal with the influence of dynamic scenes and shadows. like Figure 4 Show the system flowchart of this method, described step: based on the mixed Gaussian model of expansion, construct the probability density function (model) of background, foreground and shadow; Then by constructing the probability density function (model) of moving target and non-moving target , transforming a three-class classifi...

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 motion target detecting method based on an expanded and mixed Gaussian model, wherein the method comprises the following steps: constructing a module through a first-level model, constructing probability density functions of shadow background and prospect based on the expanded and mixed Gaussian model, constructing a module through a second-level model, constructing probability density functions of motion targets and non-motion targets based on the three models, classifying through a classifying module and through applying a MAP-MRF(Maximum a Posteriori-Markov Random Field) method, applying feedback information which is traced, and further fining the prospect model. The motion target detecting method can overcome mistake detection of prospect caused by background motion through merging space information in the Gaussian mixed model, overcomes unbeneficial influence caused by shadows through merging background modeling, prospect detecting and shadow removing in a possibility framework, thereby improving the detection effect of a motion target.

Description

technical field [0001] The invention belongs to the field of pattern recognition, relates to technologies such as image processing and computer vision, and particularly relates to the detection of moving objects in video. Background technique [0002] In the field of computer vision, one of the most fundamental problems is how to obtain high-level semantic understanding from the underlying raw video data. At present, the research on intelligent video surveillance at home and abroad mainly focuses on camera calibration, multi-camera fusion, and visual analysis of moving objects. Among them, the visual analysis of moving objects is one of the most active research topics in the field of computer vision. Its core is to use computer vision technology to detect, track and identify moving objects (such as people and cars, etc.) from image sequences and analyze their behavior. Understanding and description, it has broad application prospects in the fields of virtual reality, video ...

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 Applications(China)
IPC IPC(8): G06K9/62G06T7/00
Inventor 谭铁牛黄凯奇刘舟
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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