Multi-target tracking method and device based on video

A multi-target tracking and multi-target technology, which is applied in the field of computer vision and pattern analysis, can solve the problems of insufficient multi-target tracking and processing capabilities, and achieve the effects of maintaining effectiveness, reducing the amount of calculation, and ensuring real-time performance

Inactive Publication Date: 2012-10-24
初红霞
View PDF1 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, the particle filter has the following disadvantages in multi-mode search: First, it is weak in the continuous maintenance of multiple modes of target allocation
However, any single particle filter is not enough to deal with multi-target tracking with changing numbers.

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
  • Multi-target tracking method and device based on video
  • Multi-target tracking method and device based on video
  • Multi-target tracking method and device based on video

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The technical scheme of the present invention will be further described below in conjunction with the accompanying drawings and through specific embodiments:

[0045] Please refer to figure 1 , the present invention provides a video-based multi-target tracking method, which formulates the multi-target distribution into a mixed particle filter distribution, realizes the new particle filter by Monte Carlo through two-step recursion of prediction and update, and then uses the new particle filter Detector and Adaboost detection fusion construction multi-target tracker, including the following steps:

[0046] A. Extract the target template and initialize the parameters of the target;

[0047] B. Adaboost detection;

[0048] C. According to the motion model, dynamically predict the particle set;

[0049] D. Update the weight of each mixed component;

[0050] E. Update the motion state of each target;

[0051] F. Template update;

[0052] G. End.

[0053] Described step...

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 multi-target tracking method and device based on video. The method comprises the following steps of: extracting a target module, initiating target parameters, detecting Adaboost, carrying out dynamic prediction on a particle set according to a motion model, updating a weight value of each mixing component, updating a motion state of each target, and updating the module. A multi-mode problem in multi-target tracking can be effectively solved, the effectiveness of calculation is maintained, the multi-target tracking can be realized, and simultaneously, the requirement of instantaneity can be ensured.

Description

technical field [0001] The invention relates to the field of computer vision and pattern analysis, in particular to a video-based multi-target tracking method and device. Background technique [0002] With the development of video technology, video object tracking has become a hot research topic. It is a major direction in the field of computer vision research and the basis for advanced video applications such as behavior recognition, intelligent video surveillance, and human motion analysis. [0003] Target tracking is not a simple problem. Because the visual target itself and the surrounding environment are complex and changeable, for example, the target will be subject to light, occlusion, interference from similar backgrounds, intertwined targets, and irregular appearance, posture, shape, and movement of the target itself. The impact of interference factors such as , eventually lead to tracking failure or large deviation, so establishing a stable tracking system is a ve...

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 Applications(China)
IPC IPC(8): G06K9/62
Inventor 初红霞王希凤张鹏韩晶周强聂相举
Owner 初红霞
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