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Fast characteristic extraction system based on mass videos

A feature extraction and mass technology, applied in the field of fast feature extraction system, can solve the problems of low analysis rate and high server cost, and achieve the effect of fast analysis, adaptive load balancing, and fast feature extraction

Active Publication Date: 2015-08-19
武汉众智数字技术有限公司
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Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a fast feature extraction system based on massive video to solve the problems of low analysis rate and high server cost in the prior art

Method used

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  • Fast characteristic extraction system based on mass videos
  • Fast characteristic extraction system based on mass videos
  • Fast characteristic extraction system based on mass videos

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Embodiment Construction

[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0034] In order to illustrate the technical solution of the present invention, specific embodiments are used for description below.

[0035] Such as figure 1 Shown is a schematic structural diagram of a rapid feature extraction system based on massive videos provided by the present invention. The system includes: massive video analysis deep application module A, massive video analysis application service module B, massive video source module C, and video big Data processing module D and basic resource module E.

[0036] The massive video analysis deep application module A provides users with fas...

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Abstract

The invention is suitable for the technical field of video monitoring, and provides a fast characteristic extraction system based on mass videos. The fast characteristic extraction system based on the mass videos comprises an analysis depth application module A of the mass videos, an analysis application service module B of the mass videos, a source module C of the mass videos, a video big-data processing module D and a basic resource module E, wherein the video big-data processing module D comprises an algorithm control module F, a task segmentation module G, an algorithm injection module H, a task scheduling module I and a data storage module K; after the video big-data processing module D receives an operation task, the task segmentation module G is called according to video source information to segment the operation and package the operation into small tasks; the small tasks are issued to each cluster analysis node through the task scheduling module I; and the analysis node analyzes a video segment through the algorithm control module F and the algorithm injection module H. A plurality of severs with relatively low performance are arranged to carry out distributed processing so as to greatly lower cost and bandwidth requirements.

Description

Technical field [0001] The invention belongs to the technical field of video monitoring and relates to a rapid feature extraction system based on massive videos. Background technique [0002] Video surveillance has been widely used in many fields such as safe cities and intelligent transportation. The video surveillance market is growing every year. Front-end cameras are constantly being laid, and massive amounts of video data generated are stored in disks. [0003] When video resources need to be retrieved, fast feature extraction of massive videos is required. With the development of information technology, massive video information extraction has gradually become a hot demand. In the prior art, most video feature extraction uses a single server for processing. However, as the amount of video data for feature extraction increases, the fast feature extraction of massive videos requires high server performance and network bandwidth, and the analysis rate is not satisfactory. . Su...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 杨凡杨波贺波涛
Owner 武汉众智数字技术有限公司
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