Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Multi-view gait recognition method based on deep learning

A technology of gait recognition and deep learning, applied in the field of computer vision and machine learning, can solve problems such as missing information

Pending Publication Date: 2020-07-31
CHONGQING UNIV OF POSTS & TELECOMM
View PDF6 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Gait Energy Image (GEI) can effectively suppress the noise caused by preprocessing failure by averaging the gait contour map over a long period of time, but loses part of the temporal 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
  • Multi-view gait recognition method based on deep learning
  • Multi-view gait recognition method based on deep learning
  • Multi-view gait recognition method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0060] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0061] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...

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 relates to a multi-view gait recognition method based on deep learning, and belongs to the technical field of computer vision and machine learning, wherein the method comprises the steps: S1, collecting the gait of a person, randomly extracting n frames from each segment of video sequence, and extracting a gait contour diagram through a background subtraction method; S2, preprocessing the extracted n target contour diagrams; S3, representing periodic change by the amplitude of human motion, and detecting a contour diagram in a gait period; S4, mapping frames in the gait sequenceto different channels on the basis of the gait energy diagram of the single channel, and determining the boundary of the channel according to the amplitude of the frames; S5, combining the obtained multi-channel gait templates into a set for input, extracting features of each template, and then aggregating the features; and S6, selecting a metric learning method, proposing a Triplet Loss functionwith enhanced constraints to learn optimal features, and identifying a feature aggregation vector obtained by identification.

Description

technical field [0001] The invention belongs to the technical field of computer vision and machine learning, and relates to a multi-view gait recognition method based on deep learning. Background technique [0002] Gait recognition is a research direction that has attracted much attention in the fields of computer vision and biometric recognition in recent years. It aims to identify people based on their walking posture. Everyone has a different walking style, which is caused by the differences in 24 different components such as bone length, muscle strength, center of gravity strength and motor nerve sensitivity. If these components are taken into account, Then the gait is unique to the individual. It is precisely because of the uniqueness of each person's gait, and the use of gait to identify individuals has the advantages of long-distance, uncontrolled, and difficult to camouflage, etc., so that gait recognition technology has made great progress. There are very broad ap...

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): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/25G06N3/045G06F18/253
Inventor 吴建丁韬许镜
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com