Video frequency behaviors recognition method based on track sequence analysis and rule induction

A recognition method and sequence analysis technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of high labor cost and failure to automatically obtain event rules, and achieve the effect of saving manpower consumption

Inactive Publication Date: 2008-12-31
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF0 Cites 81 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The main problem faced by this method at present is that the event rules cannot be obtained automatically. In most rule-based reasoning work, the ...

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 frequency behaviors recognition method based on track sequence analysis and rule induction
  • Video frequency behaviors recognition method based on track sequence analysis and rule induction
  • Video frequency behaviors recognition method based on track sequence analysis and rule induction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0121] The whole learning and recognition process of this behavior understanding method is introduced above. The specific implementation process and effects of the present invention will be described below in conjunction with a specific example. in the attached Figure 8 In the traffic scene shown, we recorded a traffic video with a length of 90 minutes, which included 45 traffic light transition cycles. We hope that through automatic analysis of the vehicle trajectory flow, we can learn the traffic light rules in the normal trajectory flow. Controlled vehicle traffic transformation patterns. This access mode is provided by the attached Figure 8 As shown, the black lines with arrows in the three figures indicate the three traffic states of the T-shaped intersection, which are: "the left-turn traffic state from the auxiliary road to the main road", "the left-turn traffic state from the main road to the auxiliary road" and "the main road traffic state". State", the large tra...

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 identifying the video action based on trajectory sequence analysis and rule induction, which solves the problems of large labor intensity. The method of the invention divides a complete trajectory in a scene into a plurality of trajectory section with basic meaning, and obtains a plurality of basic movement modes as atomic events through the trajectory clustering; meanwhile, a hidden Markov model is utilized for establishing a model to obtain the event rule contained in the trajectory sequence by inducting the algorithm based on the minimum description length and based on the event rule, an expanded grammar analyzer is used for identifying an interested event. The invention provides a complete video action identification frame and also a multi-layer rule induction strategy by taking the space-time attribute, which significantly improves the effectiveness of the rule learning and promotes the application of the pattern recognition in the identification of the video action. The method of the invention can be applied to the intelligent video surveillance and automatic analysis of movements of automobiles or pedestrians under the current monitored scene so as to lead a computer to assist people or substitute people to complete monitor tasks.

Description

technical field [0001] The invention belongs to the technical fields of artificial intelligence, computer vision, pattern recognition and machine learning, and in particular relates to a behavior recognition method in videos. Background technique [0002] With the rapid development of computer technology, the new high-performance central processing unit provides computers with powerful computing capabilities, and large-capacity memory and hard disks provide computers with super data storage and reading capabilities. However, in many aspects involving human perceptual activities, such as visual function, auditory function, olfactory function, natural language understanding function, etc., the computer is still far from the level of the human brain. This status quo cannot meet the needs of some advanced applications. For example, we hope that computers can analyze human behavior in visual surveillance scenarios. When abnormal behaviors such as someone climbing over the fence, ...

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): G06K9/62
CPCG06V20/54
Inventor 谭铁牛黄凯奇张彰王亮生
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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