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

Method for recognizing human motion

A human body action recognition and human body technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve impractical problems

Active Publication Date: 2013-06-19
SHANGHAI JIAO TONG UNIV
View PDF10 Cites 53 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Because people have differences in height, body length, and behavioral posture, different people will have different ways of expressing the same action. Therefore, it is not good for an action recognition system to perform action recognition by covering all people's movement postures. practical

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
  • Method for recognizing human motion
  • Method for recognizing human motion
  • Method for recognizing human motion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0062] This embodiment provides a method for recognizing human body actions in a video sequence. The method first collects the time and space characteristics of the moving human body, and then uses the generalized Laplacian matrix to construct a graph theory semi-supervised classifier, thereby realizing the recognition of different people, Common action recognition under different angles. figure 1 It is the contour and ROI extracted when the human body is walking, where (a) is the original frame ...

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 method for recognizing a human motion in the field of computer vision and pattern recognition. Firstly, a feature containing time and space information is used for expressing the motion status of a human body in a current frame, and a classifier is designed through a graph theory semi-supervised method so that the purpose of human motion recognition is achieved. In the process of extracting the human motion feature, outline and motion light stream information in the past, in the present time and in the future is simultaneously fused so that the motion posture of a human body can be more accurately described. In addition, in order to obtain a high recognition rate with a few samples, based on the graph theory semi-supervised method of the generalized Laplacian matrix, and the graph theory semi-supervised method is used for recognizing the human motion. Experiments prove that under the conditions that observation angles are different and the motion difference of different persons exists, the method can be used for obtaining the satisfactory recognition rate of common motions.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, and in particular relates to a method for recognizing common human actions. Background technique [0002] In the field of computer vision, human action recognition is a newly emerging but very important branch. Its main purpose is to enable computers to automatically judge and understand the actions that the human body is currently performing. Since the computer itself does not have the high-level comprehension ability similar to human beings, computer action recognition is a very challenging task. However, the application prospect of action recognition is very broad. For example, it can play an important role in human-computer interaction, video conferencing, video retrieval, patient self-monitoring, intelligent security monitoring and other occasions. So research in this area is also very necessary. [0003] Due to various reasons, the existing action recognition effect ...

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): G06K9/00
Inventor 宫辰傅可人杨杰
Owner SHANGHAI JIAO TONG UNIV
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