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

Method for extracting video object under dynamic background based on fisher linear discriminant analysis

A video object, linear discrimination technology, applied in image data processing, instrumentation, calculation and other directions, can solve the problems of reducing the accuracy of global motion compensation, slow speed, and large amount of calculation for global motion estimation.

Inactive Publication Date: 2011-08-24
BEIHANG UNIV
View PDF2 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] When performing global motion estimation in the above existing technologies, sub-blocks of the entire image are often selected to participate in global motion estimation. Obviously, the calculation amount of global motion estimation is very large and the speed is relatively slow. In addition, sub-blocks that perform local motion are also inevitable. The ground will affect the global motion estimation, thereby reducing the accuracy of global motion compensation

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 extracting video object under dynamic background based on fisher linear discriminant analysis
  • Method for extracting video object under dynamic background based on fisher linear discriminant analysis
  • Method for extracting video object under dynamic background based on fisher linear discriminant analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] Such as figure 1 Shown, the extraction method of video object under a kind of moving background based on Fisher's linear discrimination of the present invention, realization steps are as follows:

[0044] Step 1. Grayscale transformation and morphological processing.

[0045] Since the grayscale information of the image contains most of the image information, in most cases, when performing spatial image processing, the color image frame is converted into a grayscale image frame. This speeds up processing and saves memory. The input video format of this experiment is YUV format, so here only need to extract Y information for processing. In addition, the morphological opening and closing reconstruction of each frame of image is to eliminate noise and smooth out some small edges to simplify the image. The results of preprocessing can be found in Figure 2c , Figure 2d with Figure 3c , Figure 3d .

[0046] Step 2. Perform block matching between frame K of the cur...

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 method for extracting a video object under a dynamic background based on fisher linear discriminant analysis. The method comprises the following steps of: dividing a K frame (namely a current frame) into a plurality of 8*8 blocks; obtaining a motion vector field of the K frame by performing block matching motion estimation on the K frame and a (K-1) frame; selecting probable background pixel blocks in the K frame as characteristic blocks; acquiring global motion model parameters from motion vectors of the characteristic blocks by a least square method; filtering exterior points by adopting Fisher linear discriminant analysis; performing global motion compensation for the current frame according to the global motion parameters; performing inter-frame difference between a rebuilt frame of the K frame and the (K-1) frame to extract a motion object. Tests prove that the extraction of the video object in a dynamic-background video sequence is realized, and the segmentation accuracy after compensation is obviously improved.

Description

technical field [0001] The invention relates to a processing method in video segmentation, in particular to a method for extracting video objects in a moving background based on Fisher linear discrimination. Background technique [0002] Video motion usually includes two types of motion information: global motion and local motion. Global motion refers to the pixel motion that occupies a relatively large proportion in the video sequence, and is generally mainly caused by the motion of the camera. It can be said that in most cases, the background itself does not move, but the background changes due to the movement of the camera. At the same time, the motion realized by the foreground object is the motion of the foreground object relative to the camera, which is called local motion. In the static background video sequence, the camera is static, there is no global motion, only the local motion of the foreground object, at this time, we can easily eliminate these static backgro...

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): G06T7/20
Inventor 祝世平马丽
Owner BEIHANG UNIV
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