A Method for Unsupervised Time-series Segmentation of Behavior Video

An unsupervised, video sequence technology, applied in image analysis, image enhancement, instruments, etc., can solve the problems of manpower and material resources, low timeliness of video monitoring and screening, etc.
CN105513095BInactive Publication Date: 2019-04-09SHANDONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHANDONG UNIV
Publication Date
2019-04-09
Estimated Expiration
Not applicable · inactive patent

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Abstract

Provided is a behavior video non-supervision time-sequence partitioning method. The method comprises steps of: initializing the initial time of video detection as nt and a corresponding sliding window frame length as Lt; detecting behavior change points in an established video sequence window; if it is detected that a behavior change point c is in the video sequence window, using a time point c as the initial time of detection and reinitializing sliding window frame length in order to continue detecting subsequent videos; if it is not detected that the behavior change point is in the video sequence window, still using the nt as the initial frame of detection, namely nt+1=nt, and updating the sliding window frame length as Lt+1=Lt+[delta]L, wherein the [delta]L is a incremented step length of the length of the sliding window; ending the method until all video frame sequences are detected or reach a predetermined deadline T0. The method makes a decision on data change points in behavior video analysis, does not require online and real-time non-supervision partition with prior knowledge, and is directly used in behavior video data online analysis.
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Description

technical field

[0001] The invention relates to an unsupervised time-sequence segmentation method of behavioral video, which belongs to the technical field of intelligent video monitoring. Background technique

[0002] Visual human behavior analysis is a key technology to realize intelligent video surveillance, human-computer interaction, medical assistance, and motion restoration. Most of the existing analysis methods assume that only one behavior category exists in an observed video clip. In practice, the observed behavior videos often contain multiple continuous behavior categories; and in many cases, we usually do not have prior knowledge to judge the possible types and the time range of each behavior, which leads to video monitoring and screening. The timeliness is very low and consumes a lot of manpower and material resources. Contents of the invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a method for unsupervised tim...

Claims

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