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Static video analysis method and system

A video analysis and static technology, which is applied in image analysis, image data processing, instruments, etc., can solve the problem that the background and foreground objects are difficult to separate, and achieve the effect of self-adaptive, compact and complete decomposition, and easy separation

Active Publication Date: 2019-12-24
GLOBAL ENERGY INTERCONNECTION RES INST CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the defect that the background and foreground objects in the prior art are difficult to separate, so as to provide a static video analysis method and system

Method used

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  • Static video analysis method and system

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Embodiment 1

[0043] Embodiments of the present invention provide a static video analysis method, which can be applied to the fields of traffic monitoring, industrial monitoring (such as defect detection of homogeneous industrial products), digital image processing and pattern recognition, such as figure 1 shown, including the following steps:

[0044] Step S1: Obtain video data.

[0045] In the embodiment of the present invention, the data video to be processed can be obtained from the camera device, and the data video to be processed is represented by X=[...,X k ,...]∈R m×n express.

[0046] Step S2: Obtain the linear dynamic regularization term of the background of the video data.

[0047] In the embodiment of the present invention, the background matrix B=[..., B k ,...]∈R m×n Represents the reconstructed background, where B k ∈ R m×τ Represents the background of a frame in the video. A linear dynamic representation matrix W is used to describe the time-varying nature of the dat...

Embodiment 2

[0132] This embodiment provides a static video analysis system, such as Figure 11 shown, including:

[0133] The video data acquisition module 1 is used to acquire video data; this module executes the method described in step S1 in Embodiment 1, which will not be repeated here.

[0134] The linear dynamic regularization item acquisition module 2 of the background is used to acquire the linear dynamic regularization item of the video data background; this module executes the method described in step S2 in Embodiment 1, which will not be repeated here.

[0135] The foreground structured sparse regularization item acquisition module 3 is used to acquire the structured sparse regularization item of the video data foreground; this module executes the method described in step S3 in Embodiment 1, which will not be repeated here.

[0136] The noise sparse regular term acquisition module 4 is used to acquire the noise sparse regular term; this module executes the method described in ...

Embodiment 3

[0141] An embodiment of the present invention provides a computer device, such as Figure 12 As shown, it includes: at least one processor 401 , such as a CPU (Central Processing Unit, central processing unit), at least one communication interface 403 , memory 404 , and at least one communication bus 402 . Wherein, the communication bus 402 is used to realize connection and communication between these components. Wherein, the communication interface 403 may include a display screen (Display) and a keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a wireless interface. The memory 404 may be a high-speed RAM memory (Ramdom Access Memory, volatile random access memory), or a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory 404 may also be at least one storage device located away from the aforementioned processor 401 . The processor 401 may execute the static video ...

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Abstract

The invention discloses a static video analysis method and system. The method comprises the following steps: acquiring video data; obtaining a linear dynamic regular term of the video data background;obtaining a structured sparse regular term of the foreground of the video data; obtaining a sparse regular term of the noise; according to the linear dynamic regular term, the structured sparse regular term of the foreground and the sparse regular term of the noise, constructing a decomposition model combining a dynamic background and structure sparsity; and performing optimization solution on the decomposition model to obtain a foreground and background separation result of the video data. The static video analysis method provided by the invention has very good background reconstruction capability and foreground detection performance under most challenging conditions, has the advantages of detection universality, high accuracy and strong robustness, has self-adaptive capability to a dataacquisition environment, and can effectively eliminate the influence of adverse factors such as noise and illumination.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a static video analysis method and system. Background technique [0002] Intelligent monitoring plays a pivotal role in urban security, traffic safety and other fields. The intelligent algorithm can strengthen the dynamic detection of various emergencies, timely warning of dangerous situations, and guide maintenance and repair of safety facilities. In recent years, the research on motion detection algorithms in static video has attracted the interest of extensive researchers, the method of pixel independent processing has been widely used, and the motion detection algorithm of low-rank background reconstruction / sparse component recovery has also been incorporated into the background model establishment and foreground detection. In earlier work, Wright et al. proposed using l 1 The norm constrains the sparse matrix and assumes that the background images are linearly relat...

Claims

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Application Information

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IPC IPC(8): G06T7/194
CPCG06T2207/10016G06T7/194
Inventor 甘津瑞高昆仑赵婷董世文吴鹏
Owner GLOBAL ENERGY INTERCONNECTION RES INST CO LTD
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