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

Method for detecting characteristics of video object in finite complex background

A complex background and feature detection technology, applied in image data processing, instruments, calculations, etc., can solve problems such as unsatisfactory real-time processing, complex structure, and large amount of calculation

Inactive Publication Date: 2009-12-23
ZHEJIANG GONGSHANG UNIVERSITY
View PDF0 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] (5) The influence of shadows: usually the shadow of the foreground target is also detected as a part of the moving target, which will affect the further processing and analysis of the moving target
[0009] The previous methods either cannot solve all the above problems, or solve them by constructing complex models, which requires a large amount of calculation and relatively high requirements on the system, and sometimes may not meet the requirements of real-time processing

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 for detecting characteristics of video object in finite complex background
  • Method for detecting characteristics of video object in finite complex background
  • Method for detecting characteristics of video object in finite complex background

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0052] (1) Take the background scene graph and compare each pixel with the existing k (kj，uv |j Calculate according to formula (2).

[0053] (2) For each image to be tested, calculate the probability of its gradient value, gradient direction and gradient vector. A gradient distribution function is established, and its distribution parameters can be calculated based on the mean and variance in the color background model in step (1). According to the gradient distribution function of each pixel, a background model based on color gradient is established. where the color gradient value is given by the formula Δ = f j , x 2 + f j ...

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 for detecting the characteristics of a video object in a finite complex background by studying color-based and gradient-based background models. The method comprises the following steps: 1, taking a background scene graph, conducting continuous training on a background sample image to obtain a color-based background model of mixed Gaussian distribution. If the background model conforms to the mixed Gaussian distribution, the gradient distribution functions of various combinations need to be calculated, and if a certain pixel belongs to any gradient distribution, the background model is supposed to conform to the gradient background model; 2, calculating the gradient distribution functions of each image to be detected, and establishing a color- and gradient-based background model; and 3, updating the parameters and weight of Gaussian distribution according to the ambient changes, such as illumination, wind strength and the like, and further updating thecolor-based models and the color- and gradient- based models. Compared with the prior art, the invention has the characteristics of background disturbance resistance and adaption to changes in environmental illumination.

Description

technical field [0001] The invention belongs to the technical field of video monitoring, and relates to a feature detection method of a video target under a limited and complex background. Background technique [0002] Moving object detection is at the bottom of the intelligent video surveillance system and is the basis for various subsequent advanced processing such as object tracking, object classification, and behavior understanding. The intelligent video monitoring system uses a static camera to monitor a fixed area in real time. Its purpose is to segment dynamic targets from the static background, and perform operations such as classification and tracking on them. For static cameras, background modeling is an effective method to solve real-time segmentation of dynamic objects. [0003] An effective background model should be able to overcome the following problems that often exist in practical applications: [0004] (1) Extraction of the background model: The simplest...

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): G06T7/00
Inventor 琚春华刘东升周怡郑丽丽王蓓王冰陈沛帅肖亮
Owner ZHEJIANG GONGSHANG UNIVERSITY
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