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

Method for automatically detecting abnormal behaviors of video moving object based on change of movement features

A technology of moving objects and moving features, applied in image data processing, instruments, character and pattern recognition, etc., can solve the problem of low robustness of abnormal behavior detection results

Inactive Publication Date: 2014-08-20
SHANGHAI UNIV
View PDF2 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an automatic detection method for abnormal behavior of video moving objects based on changes in motion characteristics in view of the problems that the results of the current abnormal behavior detection method for moving objects are obviously affected by the external environment, and the robustness of abnormal behavior detection results is low.

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 automatically detecting abnormal behaviors of video moving object based on change of movement features
  • Method for automatically detecting abnormal behaviors of video moving object based on change of movement features
  • Method for automatically detecting abnormal behaviors of video moving object based on change of movement features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] see figure 1 , the method for automatic detection of abnormal behavior of video moving objects based on changes in motion characteristics is characterized in that the operation steps are as follows:

[0057] (1) Start the image acquisition system for abnormal behavior detection of moving objects: collect video images;

[0058] (2) Calculation of particle motion flow field;

[0059] (3) Particle motion feature extraction;

[0060] (4) Clustering of particle motion features;

[0061] (5) Abnormal behavior detection.

Embodiment 2

[0063] This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0064] The specific operation steps of the calculation of the particle motion flow field in the step (2) are as follows:

[0065] (2-1) Optical flow field calculation: collected by the camera t Two consecutive adjacent frames of images at any time, calculate the optical flow field in the horizontal x component of direction u ( t ): perpendicular to the optical flow field y component of direction v ( t ): ;

[0066] (2-2) Particle flow field calculation:

[0067]

[0068] in, , Particles respectively P exist t +1 moment in level x orientation and vertical y position in the direction, , Particles respectively P exist t always on level x orientation and vertical y position in the direction.

[0069] The specific operation steps of described step (3) particle motion feature extraction are as follows:

[0070] (3-1) Calculation of average motion v...

Embodiment 3

[0081] see Figure 1 to Figure 5 , this embodiment is: the operating procedure such as figure 1 As shown, the original frame of image in this example is as follows figure 2 shown, yes figure 2 The video image sequence shown uses dynamic particle flow to describe the motion state of the moving object in the video image, and establishes a motion feature space based on the particle flow field. Class mode to realize the automatic detection of abnormal behavior of video moving object motion feature changes. Specific steps are as follows:

[0082] (1) Start the image acquisition system for abnormal behavior detection of moving objects: collect video images;

[0083] (2) Calculation of the flow field of particle movement: Two consecutive adjacent frames of images collected by the camera (image size: 320′240), calculate the optical flow field ( u ( t ), v ( t )),Such as image 3 shown; right image 3 As shown in the image, the particle flow field is calculated as Figure...

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 method for automatically detecting abnormal behaviors of a video moving object based on change of movement features. In the method, the change state of the movement features of the video moving object can be reflected according to flow of particles in a Lagrangian particle dynamical system, extraction and clustering analysis are carried out on movement features of the particles to determine the intimacy degree of the classes of the movement features of the particles, and whether the abnormal behaviors of the video moving object occur is automatically detected based on the fact that when the abnormal behaviors of the video moving object occur, the classes of the movement features of the particles of the video moving object are different form the classes of movement features of particles with normal behaviors. By means of the method, it is not required that the moving object is tracked and abnormal behavior samples of the moving object are collected in advance and trained, and automatic detection of the abnormal behaviors of the video moving object can be achieved under various conditions.

Description

technical field [0001] The invention relates to an automatic detection method for abnormal behavior of video moving objects based on changes in motion characteristics, which is used for public safety and prevention, and video digital image analysis and understanding. It belongs to the technical field of intelligent information processing. Background technique [0002] With the rapid growth of urban population and the increasingly complex urban environment, urban social security emergencies such as mass incidents, riots, and terrorist attacks have seriously affected urban public safety. Building a harmonious and safe society has become an important topic in today's international society. [0003] In recent years, as security issues have received increasing attention from the society, the demand for video surveillance systems is gradually expanding, through real-time monitoring of targets staying or passing by in specific scenes, and semantic analysis of the behavior of movin...

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): G06K9/62G06T7/20
Inventor 管业鹏仉长崎许瑞岳
Owner SHANGHAI UNIV
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com