Target tracking method based on HSV color covariance characteristics

A technology of target tracking and target tracking window, applied in image analysis, instrument, calculation, etc., can solve the problems of poor mutual independence between features, low accuracy and robustness, poor stability of tracking system, etc., to enhance mutual independence , the effect of reducing information redundancy and enhancing stability

Inactive Publication Date: 2014-08-13
XIDIAN UNIV
View PDF4 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the actual situation, these traditional methods have high similarity between the extracted features, poor mutual independence between features,

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
  • Target tracking method based on HSV color covariance characteristics
  • Target tracking method based on HSV color covariance characteristics
  • Target tracking method based on HSV color covariance characteristics

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] refer to figure 1 , the specific implementation process of the present invention comprises the following steps:

[0045] Step 1. Initialize particles, target tracking windows and feature templates.

[0046] 1.1) Initialize particles: Let the initial moment k=1, according to the initial state X of the target 0, generate N particles to form a particle set at time k-1 in Indicates the estimated state value of the i-th particle at time k-1, Obeying the mean is X 0 Gaussian distribution with variance Ψ, X 0 is the initial state of the target, Ψ is the process noise variance, i represents the serial number of the particle, and N represents the total number of particles;

[0047] 1.2) Initialize target tracking window: B k-1 =(r k-1 ,c k-1 ) T , where r k-1 and c k-1 Respectively represent the length and width of the target tracking window at time k-1, and T represents the vector transpose;

[0048] 1.3) According to the initial state of the target and the targ...

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 target tracking method based on HSV color covariance characteristics. The method mainly solves the problems that according to an existing tracking technology, the characteristics extracted from a color image target are large in information redundancy and poor in independence. The method comprises the implementation steps of firstly obtaining a candidate target under a particle filter framework through the target state predication, extracting hue, saturability, brightness and Laplacian response of a candidate target image to serve as the apparent characteristics, performing fusion to build a covariance operator, adjusting a tracking window and updating a characteristic template by calculating the similarity weight of the candidate target characteristics and the template, and finally updating the target state and effectively tracking the target according to the weight fusion candidate target. According to the method, the information redundancy of the target characteristics can be effectively reduced, the independence between the characteristics can be enhanced, the precision and robustness of target feature description can be improved, and the real-time precise tracking on a color image target can be achieved.

Description

technical field [0001] The invention belongs to the technical field of tracking and monitoring, and in particular relates to a color image target tracking method, which can be used in systems such as video tracking and target monitoring. Background technique [0002] Color images, because of their rich image details and low cost of photosensitive devices, are widely used in practice. Therefore, target tracking for color images has broad application prospects and practical significance. Rich image details not only provide a lot of material for target feature description, but also bring difficulty in feature selection. How to fully mine the image information of the target, remove the redundancy, effectively organize and build a multi-feature description model has become a key issue in the research of color image target tracking. [0003] At present, the feature description models for color target tracking mainly include: joint feature histogram, covariance operator, etc. in:...

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): G06T7/20G06T7/40
Inventor 姬红兵樊振华刘月王磊
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap