Multi-target tracking method in video surveillance

A multi-target tracking and video monitoring technology, applied in the field of multi-target tracking, can solve problems such as target loss, real-time defects, and lack of anti-affine performance, and achieve the effect of satisfying real-time performance and reducing the amount of calculation

Active Publication Date: 2014-12-10
重庆信科设计有限公司
View PDF5 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this technology does not have high anti-affine performance, and there are also deficiencies in target matching accur

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 in video surveillance
  • Multi-target tracking method in video surveillance
  • Multi-target tracking method in video surveillance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] Combine figure 1 , A multi-target tracking method in video surveillance, which uses the adjacent frame difference method to detect moving targets, establishes a tracking target model for the detected moving targets, and builds the ASIFT feature vector of the target model; uses particle filtering to predict the target in the candidate area , And establish the ASIFT feature vector of the candidate target model, match the tracking target feature vector with the target feature vector of the candidate area, use the RANSAC algorithm to eliminate the wrong matching, update the target model, and achieve target tracking, including the following steps:

[0047] Step A: Read the initial frame of the video image, and use the adjacent frame difference method to detect the moving target in the video sequence; the read video image is the video collected by the surveillance camera.

[0048] Read the initial frame of the video image, and calculate the difference between the corresponding pix...

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 video target tracking method capable of integrating ASIFT features and particle filter, and belongs to the technical field of video information processing and mode recognition. The video target tracking method comprises the following steps: the adjacent frame difference method is utilized to obtain moving objects in a video sequence; according to the area corresponding to an acquired complete target, a tracking target model is established; ASIFT feature vectors of the target model are established; the particle filter technology is adopted to predict a candidate area target; ASIFT feature vectors of a candidate target model are established; the feature vectors of the tracking targets are matched with the feature vectors of the candidate target; the RANSAC algorithm is adopted to reject wrong matching; the target model is renewed, so as to realize target tracking. The video target tracking method provided by the invention can accurately and quickly track the targets under the condition that brightness changes and is shielded. Therefore, the multi-target tracking method in the video surveillance has relatively good real-time performance and robustness.

Description

Technical field [0001] The invention belongs to the technical field of video information processing and pattern recognition, in particular to a multi-target tracking method in video surveillance. Background technique [0002] Target tracking has always been the foundation of machine vision, artificial intelligence and pattern recognition. Target tracking can be widely used in industries such as navigation and positioning, military guidance, and security monitoring. [0003] Target tracking is to use the known target location information and target continuity to find a moving target of interest on a sequence of images. At present, there are many target tracking methods in video surveillance, such as tracking methods based on particle filtering, tracking methods based on Mean Shift, and target tracking methods based on Kalman filtering. However, in these traditional methods, when the target is occluded and there is interference in the surrounding environment (such as noise, light),...

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 杨丰瑞窦绍宾吴翠先刘欣
Owner 重庆信科设计有限公司
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