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

Self-adaptation mean-shift target tracking method based on optical flow field estimation

A target tracking and adaptive technology, applied in the field of image processing

Inactive Publication Date: 2012-11-28
刘怡光
View PDF2 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But both have their own shortcomings in adaptive tracking

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
  • Self-adaptation mean-shift target tracking method based on optical flow field estimation
  • Self-adaptation mean-shift target tracking method based on optical flow field estimation
  • Self-adaptation mean-shift target tracking method based on optical flow field estimation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] specific implementation plan

[0021] Below in conjunction with accompanying drawing, the implementation of method is described in further detail:

[0022] 1. If figure 1 As shown, the white points in the middle two pictures are the feature points of the two frames before and after obtained by the optical flow method, and the displacement information can be obtained from the position information, and the final optical flow map is marked with a white line in the bottom picture. Most of the lines correctly indicate the direction of the target's movement. Therefore, the optical flow method can effectively obtain the characteristics of the motion information of the feature points, and can calculate the moving speed and direction of the target. First find some feature points in the target window, and then use the optical flow constraint equation ,in Indicates brightness, , is the partial derivative of the image, is the derivative of the image over time, and calcu...

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 self-adaptation mean-shift target tracking method based on optical flow field estimation. Aiming to solve the problem that the tracking fails due to high motion speed of the target or obvious scale variation and shielding of the target during target tracking of the mean-drift shift algorithm, a light stream method is introduced on the basis of a traditional mean-shift vector method, feature points are searched on the target, the centre position and size of a window are modified and tracked based on the variation information of the feature point, and more accurate length and width of the window can be obtained through self-adaptation by a Bhattacharyya coefficient bisection method. The area of the object shielded by a stationary object can be observed through aberration analysis, and the object can be recaptured by using the Bhattacharyya coefficient.

Description

technical field [0001] The invention relates to a target tracking algorithm, in particular to an adaptive Mean-Shift target tracking method based on optical flow field estimation, belonging to the field of image processing. Background technique [0002] Object tracking method is one of the important research directions in the field of image processing, and it has been widely used in the fields of public security, intelligent transportation, and object positioning. For this reason, many researchers at home and abroad have been working on the research of this project. Target tracking is generally based on the processing of image sequences, identifying the target from the complex background, and predicting the movement rules of the target to achieve continuous and accurate tracking of the target. [0003] With the rapid development of computer technology and image algorithm research, target tracking methods have also made great progress, and the Mean-Shift algorithm has...

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 刘怡光曹丽萍李剑锋
Owner 刘怡光
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