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

Video motion characteristic extraction method based on fuzzy concept lattice

A motion feature extraction and fuzzy concept technology, applied in image data processing, instruments, calculations, etc., can solve the problem of not being able to distinguish the motion features of the target frame well, so as to improve the efficiency of feature extraction, improve accuracy, and reduce weight. shadow effect

Inactive Publication Date: 2013-04-03
XIDIAN UNIV
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is based on multi-scale wavelet transform for moving target detection, which can effectively suppress the shadow problem of the target, automatically select the optimal threshold, and does not require complex supervised learning or manual calibration. However, reference frames are needed when extracting motion features. If the frame contains motion features, motion ghosting will be generated on the target frame, and the motion features of the target frame cannot be well distinguished

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
  • Video motion characteristic extraction method based on fuzzy concept lattice
  • Video motion characteristic extraction method based on fuzzy concept lattice
  • Video motion characteristic extraction method based on fuzzy concept lattice

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] 1. Introduction to basic theory

[0034] 11 Related Theories of Fuzzy Concept Lattice

[0035] Fuzzy concept lattice is a clustering analysis method based on lattice theory, which obtains the corresponding conceptual structure by clustering the relationship between objects and attributes under the background of a specific form in a certain field. In the fuzzy concept lattice, the relationship between conceptual attributes and objects is an uncertain fuzzy relationship, such as "young people have high consumption levels", where "young people" is an object, which is a fuzzy set, and "high consumption level" is an attribute It can only be described by the degree of affiliation. The consumption level involves income, basic necessities of life, family burden, culture and entertainment, etc. It is a fuzzy set of multiple attributes. At present, domestic and foreign scholars have done a lot of research on the construction algorithm of fuzzy concept lattice. Among them, Liu Zo...

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 motion characteristic extraction method based on a fuzzy concept lattice, which is mainly used for solving the problems of background interference and motion ghost existing in the conventional method. The method comprises the following implementation methods of: firstly, partitioning a video shot, generating a motion characteristic association rule of all lenses byusing the fuzzy concept lattice and extracting an interesting lens according to the association rule; secondly, generating a motion characteristic association rule of all target frames in the interesting lens by using the fuzzy concept lattice and extracting an interesting target frame according to the association rule; and lastly, extracting the motion characteristic of the interesting target frame according to fuzzy concept lattices of all image blocks in the interesting target frame. According to the method, the video motion characteristic can be extracted quickly; and the method can be applied to occasions needing to process mass video data such as target tracking, video monitoring and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to video motion feature extraction, and can be used in video processing fields such as target tracking and video monitoring. Background technique [0002] Video motion feature is one of the important features of video. It is widely used in video processing fields such as object tracking and video surveillance. At present, research on video motion feature extraction has made great progress. However, with the rapid growth of massive video data, how to Quickly and accurately extracting video motion features has become a difficult problem that needs to be solved urgently. [0003] At present, there are mainly the following methods for extracting video motion features: [0004] (1) Duan-Yu Chen, Kevin Cannons, Hsiao-Rong Tyan, Sheng-Wen Shih, Hong-Yuan Mark Liao. Spatiotemporal motion analysis for the detection and classification of moving targets. IEEE Transactions on multimedia, 20...

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 Patents(China)
IPC IPC(8): G06T7/20
Inventor 同鸣冯向玲姬红兵
Owner XIDIAN 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