Multi-target tracking method based on layered hypergraph optimization

A multi-target tracking and monitoring target technology, which is applied in the field of multi-target tracking based on hierarchical hypergraph optimization, can solve the problems of being unable to effectively identify targets with similar appearances, and cannot deal with long-term occlusion problems, and reduce the amount of calculation , high reliability effect

Inactive Publication Date: 2014-05-07
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF3 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is that the current multi-target tracking method cannot dea...

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 based on layered hypergraph optimization
  • Multi-target tracking method based on layered hypergraph optimization
  • Multi-target tracking method based on layered hypergraph optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention mainly proposes a multi-target tracking method based on hierarchical hypergraph optimization. By considering the information of the relationship between multiple detection results across the time domain, the detection results of a global time domain can be associated to form the target trajectory through the method of data association without knowing the number of targets in advance, so as to complete The task of multi-object tracking.

[0023] The invention proposes to regard the task of multi-target tracking as a clustering problem on an affinity graph or a hypergraph with a dense neighbors search method. Hypergraph is a generalized form of traditional graph (Pairwise graph), that is, a graph whose edges are composed of multiple vertices instead of just two points. Hereinafter, we will collectively refer to traditional graphs and hypergraphs as "graphs". The affinity graph describes the probability that suspected target regions (target local tr...

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 multi-target tracking method. The multi-target tracking method comprises the steps that S1, a video is divided into time quanta in the time domain, target detection is carried out on each video frame, and the detection results serve as suspected target areas; S2, the positions of the suspected target areas obtained in the S1 serve as vertexes, otherwise, local tracks in the time quanta serve as vertexes, the relation between the local tracks serves as edges, and an affinity graph of the local tracks is built; S3, a plurality of intensive neighbor kinds are obtained from the affinity graph in a searching mode, and the local tracks belonging to the same intensive neighbor kind serve as local tracks belonging to the same target; S4, unit time quanta belonging to the same time quantum are aggregated to form a plurality of new unit time quanta, and local tracks, belonging to the same intensive neighbor kind, in the same new unit time quantum are merged to form a merging track; S5, whether a single time quantum has crossed the whole tracking time domain or not is judged, if yes, the merging track obtained at present serves as a tracking track of a monitored target, and if not, the S2 is executed.

Description

technical field [0001] The invention relates to the fields of image processing, pattern recognition and computer vision, in particular to a multi-target tracking method based on hierarchical hypergraph optimization. Background technique [0002] Multiple object tracking is an important but difficult problem in computer vision. Although existing tracking methods partially solve the tracking difficulties to varying degrees, their performance in practical applications is often unsatisfactory. Recently, due to the rapid development of object detection technology, multi-object tracking methods based on data association have gradually become mainstream. Given the object detection results of each frame of image, the multi-object tracking problem can be modeled as the process of associating multiple object detection results from different frames and forming a continuous trajectory. [0003] In practical applications, the relationship between multiple detection results across the t...

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 李子青雷震易东文珑银
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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