Monitoring scene multi-target tracking method and system

A multi-target tracking and scene technology, applied in the real-time tracking method and system field of multiple targets in the monitoring scene, to reduce complexity, achieve a balance between complexity and precision, and achieve the effect of adjustment

Active Publication Date: 2020-01-07
HANGZHOU WEIMING XINKE TECH CO LTD +1
View PDF2 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the original multi-hypothesis tracking algorithm, although the maximum independent subset sum algorithm (MWIS) will prune the hypothesis tree, the number of hypotheses for each target will still multiply geometrically over time before reaching the pruning time point. growth, it is difficult to make judgments based on long-term hypothetical information

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
  • Monitoring scene multi-target tracking method and system
  • Monitoring scene multi-target tracking method and system
  • Monitoring scene multi-target tracking method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0028] The assumption in the present invention refers to that, because of the inaccuracy usually brought by the detection algorithm, the multi-hypothesis tracking algorithm will maintain a hypothesis of the possible location of the target for each target. The affiliation of hypotheses between different frames constitutes a hypothesis tree. The actual position of the target in a certain frame needs the information of multiple frames...

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 monitoring scene multi-target tracking method and system, and the method is based on the multi-hypothesis tracking after pruning optimization, and comprises the following steps: receiving a target detection frame of a current frame; based on the target detection box of the current frame, generating assumptions of possible positions of each target; solving the maximum independent subset and problem based on all hypotheses of a plurality of recent frames, obtaining hypothesis paths which can be selected by each target and do not conflict with each other, and outputtingthe position of each target before the plurality of frames; and performing pruning optimization by combining the maximum independent subset, the solution of the problem and a Hungary algorithm to obtain a multi-target tracking result. The invention provides a novel pruning optimization method, so that the complexity of a multi-hypothesis tracking algorithm is greatly reduced. For multi-target tracking of a monitoring scene, CPU resources can be fully utilized, GPU resources are not occupied, and multiple targets are tracked in real time; and the adjustment of algorithm complexity and precisionbalance can be realized by changing the length of information integration time.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a real-time tracking method and system for multiple targets in a monitoring scene. Background technique [0002] In the process of intelligent analysis of surveillance video, the usual process is to extract the detection frame of the target, and give each target its own unique identification code through the multi-target tracking method to distinguish different targets. Multi-target tracking method is a very classic problem in the field of computer research. Usually the algorithm converts the tracking problem into a graphical model for solution. However, it is usually difficult to flexibly adjust the balance between the accuracy and speed of the algorithm. Most of the improvements in multi-object tracking methods in recent years are based on deep learning-based feature extraction methods. By introducing a deep feature extraction network into the multi-target tracking method,...

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): G06K9/00H04N7/18
CPCH04N7/18G06V20/41
Inventor 林小涵黄晓峰殷海兵贾惠柱
Owner HANGZHOU WEIMING XINKE TECH CO LTD
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