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

A method of video target tracking using two-layer cascaded boosting classification algorithm

A classification algorithm and target tracking technology, applied in the field of image processing, can solve the problems of single Haar-like feature construction template, loss of image color and texture details, etc.

Active Publication Date: 2018-05-15
EAST CHINA NORMAL UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with the traditional method, the present invention uses multiple filters to extract features from the image block, expresses the features of the image block more finely, and solves the problem of using a Haar-like feature to construct a single template and losing image color and texture details; in addition , the proposed tracking method uses a two-layer cascaded structure to select the filter type and image block position separately, and make the selected features suitable for the tracking task as much as possible

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
  • A method of video target tracking using two-layer cascaded boosting classification algorithm
  • A method of video target tracking using two-layer cascaded boosting classification algorithm
  • A method of video target tracking using two-layer cascaded boosting classification algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments.

[0054] refer to figure 1 , the implementation process of the present invention includes the following steps: one is the preprocessing process of the image to obtain the target sample and the image block in the target area; the other is to extract features through the filter to obtain the feature pool of positive and negative samples; the third is to include online features The two-layer Boosting cascade algorithm for selection and weight training; the fourth is target tracking through classifier detection. Specific process:

[0055] 1. Preprocessing of video tracking

[0056] In the first frame of the image sequence, the target area for tracking is first marked. A number of image blocks with sizes and relative positions are randomly generated in the target area. Use the convolution kernel group of t...

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 discloses a method for realizing video target tracking by using a two-layer cascaded Boosting classification algorithm. The method includes: image preprocessing, obtaining target samples and image blocks in the target region; extracting features through filters to obtain positive and negative The feature value of the sample; the two-layer Boosting cascade algorithm including online feature selection and weight training; the target tracking of classifier detection and other steps. The present invention uses multiple filters to extract features from image blocks, expresses the features of image blocks more finely, and solves the problem of using a single Haar-like feature to construct a template and losing image color and texture details; in addition, using two-layer cascaded structure, the filter type and image block location are selected separately, so that the selected features are more suitable for tracking tasks.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a method for realizing video target tracking by using a two-layer cascaded Boosting classification algorithm. Background technique [0002] Video-based object tracking technology is a classic problem that many scholars in the field of computer vision and image processing pay attention to. With the rapid development of technologies such as computer storage, network communication, and image processing, video tracking technology has also made great progress. [0003] It is very challenging to design a stable and efficient target tracking algorithm. The difficulty mainly comes from the influence of factors such as complex background, target occlusion, and target deformation and rotation in the application. The current popular algorithms are mainly divided into two categories: generative and discriminative. The generation method uses the tracking target as a feature to constr...

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 Patents(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T2207/10024G06T2207/10016G06F18/241
Inventor 瞿恺孙力徐姗姗
Owner EAST CHINA NORMAL 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