WO2022016587A1 - 基于互联网大数据的数字视频制作系统 - Google Patents

基于互联网大数据的数字视频制作系统 Download PDF

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Publication number
WO2022016587A1
WO2022016587A1 PCT/CN2020/105301 CN2020105301W WO2022016587A1 WO 2022016587 A1 WO2022016587 A1 WO 2022016587A1 CN 2020105301 W CN2020105301 W CN 2020105301W WO 2022016587 A1 WO2022016587 A1 WO 2022016587A1
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module
database
video
classification
information
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PCT/CN2020/105301
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English (en)
French (fr)
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高岩
赵金玲
陈小兵
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南京智金科技创新服务中心
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/75—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/71—Indexing; Data structures therefor; Storage structures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
    • H04N21/44016—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving splicing one content stream with another content stream, e.g. for substituting a video clip
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H04N5/265—Mixing

Definitions

  • the present application relates to the technical field of video production, in particular to a digital video production system for intelligently and automatically generating videos based on Internet big data.
  • the production process of digital video usually adopts the process of manual processing by highly professional professionals.
  • the degree of automation of video production is low and the degree of specialization is high.
  • the degree of intelligent automation of the virtual studio system using keying and synthesizing video is not high, and it is only suitable for TV stations to produce professional programs.
  • the purpose of this application is to provide a digital video production system based on Internet big data, which adopts an intelligent system to automatically generate customized videos, and solves the problems of low automation degree and high professional threshold in the existing solutions.
  • the digital video production system based on Internet big data in this application includes a server, and the server includes a data search and collection module, a material database, a material classification management module and a video generation module;
  • the data search and acquisition module is used for inputting and storing the material collected from the Internet in the material database;
  • the material classification management module is used for invoking the data information of the material database for classification and arrangement;
  • the video generation module is used for invoking the classified data information of the material classification management module for video production.
  • the material classification management module includes a material subject classification module and a material feature analysis module;
  • the material subject classification module includes a plurality of subject classification material databases, and the material subject classification module classifies the data information of the material database into the multiple subject classification material databases according to the set subject type;
  • the material feature analysis module includes a plurality of feature classification material databases, and the material feature analysis module assigns the data information of the subject classification material database according to the set feature type and then classifies them into the plurality of feature classification material databases.
  • the video generation module includes a material random sorting module and a video database, and the material random sorting module is used for randomly sorting and splicing the acquired data information of the feature classification material database according to a set algorithm to generate video information and store it in the video database. .
  • the material database includes a background material database and a main material database
  • the subject classification material database includes a background subject classification material database and a main subject classification material database.
  • the feature classification material database includes a background feature classification material database and a subject feature classification material database.
  • the video generation module further includes a video keying and synthesis module, and the video keying and synthesis module is configured to perform keying and synthesis processing on the background video information and the main video information generated by the material random sorting module to generate The synthesized video information is stored in the video database.
  • the digital video production system further includes a subtitle generation module for adding subtitles to the video.
  • the subtitle generation module includes an external editing module, a subtitle import module and a subtitle information database;
  • the external editing module is used to input and store the subtitle data information into the subtitle information database through the data upload port;
  • the subtitle importing module is used for retrieving the data information of the subtitle information database and importing the composite video to generate the subtitle composite video and store it in the video database.
  • the present application adopts an intelligent system to automatically generate a customized video, which has the following characteristics compared with the prior art:
  • the material comes from Internet big data, with a wide range of materials, complete data and information, and diverse forms of expression; (4) Intelligent automatic video synthesis, flexible, efficient, and practical, which greatly improves production efficiency and makes video program production more colorful.
  • the digital video production system based on Internet big data in this application has the characteristics of high degree of automation and easy operation.
  • FIG. 1 is a schematic block diagram of a digital video production system based on Internet big data in Embodiment 1 of the present application.
  • FIG. 2 is a schematic structural diagram of a cabinet in Embodiment 2 of the present application.
  • the digital video production system based on Internet big data in this embodiment is basically as shown in Figure 1, including a server connected to the Internet.
  • the server includes a data search and collection module, a material database, a material classification management module, a video generation module, and a material classification module.
  • the management module includes a material subject classification module and a material feature analysis module.
  • the material theme classification module includes multiple subject classification material databases
  • the material feature analysis module includes multiple feature classification material databases
  • the video generation module includes a material random sorting module and a video database.
  • the data search and collection module inputs the materials collected from the Internet and stores them in the material database.
  • the data search and collection module can search and download related data information on the Internet platform according to keyword search or other set search conditions and algorithms, and input after preliminary screening. system.
  • the material classification management module calls the data information of the material database for classification.
  • the material subject classification module classifies the data information of the material database into a plurality of subject classification material databases according to the set theme type.
  • the material feature analysis module assigns the data information of the subject classification material database to a plurality of feature classification material databases after assigning values according to the set feature type.
  • the video generation module calls the data information of the feature classification material database to make video.
  • the material random sorting module performs random sorting and splicing of the acquired data information of the feature classification material database according to the set algorithm to generate video information and store it in the video database.
  • the above solution uses an intelligent system to automatically generate customized videos, classify and mark materials according to themes and features to generate customized videos according to a set algorithm, with a low operating professional threshold and a high degree of automation.
  • the material database in this solution includes a background material database and a main material database.
  • the subject classification material database includes the background subject classification material database and the main subject classification material database.
  • the feature classification material database includes a background feature classification material database and a subject feature classification material database.
  • the video generation module also includes a video keying and synthesizing module. The video keying and synthesizing module performs keying and synthesizing processing on the background video information and the main video information generated by the material random sorting module to generate the synthesized video information and stores the synthesized video information in the video database.
  • the digital video production system in this scheme also includes a subtitle generation module, the subtitle generation module includes a subtitle import module and a subtitle information database, the external editing module inputs and stores the subtitle data information in the subtitle information database through the data upload port, and the subtitle import module adjusts the subtitle information database. Take the data information of the subtitle information database and import it into the composite video to generate the subtitle composite video and store it in the video database.
  • the subtitle generation module includes a subtitle import module and a subtitle information database
  • the external editing module inputs and stores the subtitle data information in the subtitle information database through the data upload port
  • the subtitle import module adjusts the subtitle information database. Take the data information of the subtitle information database and import it into the composite video to generate the subtitle composite video and store it in the video database.
  • the digital video production system based on Internet big data in this embodiment is suitable for non-professional applications, has a flexible and diverse and practical feature material database, and makes video production intelligent and automatic.
  • This system characterizes the digital video materials stored in various storage media of the computer.
  • Features refer to the description of various characteristics, characteristics, and states of landscapes and objects in the landscape. Layout, color, old and new, motion state, ambient temperature, light and shade, color, season, time, etc., the degree of characteristics can be marked with numbers or words.
  • the video generation module performs feature adaptation operation and theme limitation, intelligently and automatically produces video programs, and can output different results by setting the algorithm of the system.
  • the customized content of the video is to use the background of Tiananmen Square in Beijing 10 years ago to reproduce the character's activity scene, just input this requirement into the system for theme matching and feature adaptation, and automatically create a background template that meets its requirements.
  • Compositing technology places characters into the scene to create customized videos that satisfy users.
  • the videos produced each time are different, but they all conform to the logic of the algorithm.
  • the background video can be rotated from left to right to show the Tiananmen landscape, or it can be rotated from right to left. Thereby giving users a different service experience.
  • this solution has the following characteristics: (1) It adopts characterization technology to describe the characteristics of video materials and establishes a feature database; (2) It makes it possible for digital video production to develop from specialization to popularization, and users can make videos easily and freely; (3) Source of material For Internet big data, it has a wide range of materials, complete data and information, and diverse forms of expression; (4) intelligent automatic video synthesis, flexible, efficient, and practical, greatly improving production efficiency and making video program production more colorful.
  • FIG. 2 of the description includes cabinet 1 , air outlet 2 , fan 3 , spring 4 , first electromagnet 5 , air inlet 6 , second electromagnet 7 , and door panel 8 .
  • the server in order to improve the processing capacity to cope with tasks such as digital video production that require high processing capacity, the server adopts a plurality of blade servers, which are described as follows.
  • the cabinet 1 shown in FIG. 2 the cabinet 1 further includes an air outlet 2 , a fan 3 , a spring 4 , a first electromagnet 5 , an air inlet 6 , a second electromagnet 7 and a door panel 8 .
  • FIG. 2 there are two cabinets 1 in this embodiment, and the left and right mirrors are symmetrical.
  • the space inside the cabinet 1 is divided into four layers, and each layer is placed with two devices (the cabinet 1 is not shown in FIG. 2 ). the spatial structure and placement of equipment).
  • the structure of the cabinet 1 on the left is used for description, and the structure of the cabinet 1 on the right is similar to the structure of the cabinet 1 on the left, which is not repeated in this embodiment.
  • Blade servers often encounter problems of excessive temperature, especially when the server is working under an overclocked state, and it is necessary to properly handle the cooling problem.
  • Server overclocking needs to increase the working voltage of the CPU, and the increase in the working voltage will increase the power consumption, which will naturally increase the heat generation.
  • the CPU temperature will no longer rise, and the heat generation is determined by the power of the CPU, which is proportional to the voltage.
  • the ambient temperature, fan quality, and host environment also have a great impact on the cooling effect. It can be seen that it is very likely that the calorific value of the equipment in the cabinet 1 on the left and the right is different.
  • the cabinet 1 is in the shape of a cuboid, an air outlet 2 is opened at the top of the cabinet 1 , and two air inlets 6 are opened at the bottom of the cabinet 1 .
  • Two fans 3 are also installed at the bottom of the cabinet 1 , and the fans 3 are symmetrical with respect to the vertical symmetry line of the cabinet 1 .
  • the specific installation method of the fan 3 is that the fan 3 is made of metal material, and the fan 3 is fixed on the bottom surface of the cabinet 1 by two springs 4. One end of the spring 4 is welded to the fan 3, and the other end is welded to the bottom of the cabinet 1.
  • the fan 3 Located just above the air inlet 6.
  • the first electromagnet 5 includes an iron core and a coil. The coil is made of conductive material and wound on the iron core.
  • the first electromagnet 5 is installed on the left side of the spring 4 that supports the right side of the fan 3.
  • the specific method is iron core welding. at the bottom of cabinet 1.
  • a door panel 8 is provided, and the door panel 8 is hinged on the cabinet 1 .
  • the second electromagnet 7 includes an iron core and a coil, the coil is made of conductive material, wound on the iron core, and the iron core is welded on the door panel 8 .
  • a temperature sensor is also installed at the air outlet 2 to collect the temperature value of the air flow at the air outlet 2; the energized and disconnected states of the coils of the first magnet 5 and the second magnet 7 are determined by the control module.
  • the control is performed by a control switch, and the specific control switch may refer to the prior art.
  • the door panels 8 of the cabinet 1 on the left and right sides are in a closed state, and the air outlet 2, the air inlet 6 and the fan 3 are in an open state.
  • the temperature sensors at the air outlet 2 on the left and right cabinet 1 detect the temperature value of the airflow at the air outlet 2 in real time, and send the detected temperature value to the judgment module.
  • the judgment module judges the temperature value of the airflow at the air outlet 2 of the left and right cabinet 1: if the temperature value of the airflow at the air outlet 2 of the left and right cabinet 1 is the same, it means that the fan 3 in the left and right cabinet 1
  • the heat dissipation effect is basically the same, so no additional operation is required.
  • the control module sends a signal to the control switch, first turns on the switches of the coils of the second electromagnet 7 on the left and right cabinet 1, and then turns on the first electromagnet 5 on the left cabinet 1. Coil switch. In this way, the door panels 8 of the left and right cabinets 1 will approach each other under the mutual attraction of the second electromagnet 7, so that the door panels 8 are in an open state; the fan 3 of the left cabinet 1 will be in the first electromagnet 5.
  • the control module sends a control command to reduce the rotational speed to the left fan 3 in the left cabinet 1 .
  • the rotational speed of the left fan 3 in the left cabinet 1 will be reduced, so that the air flow entering from the air inlet 6 below the fan 3 is reduced, so as to realize the shunting of the intake air and effectively improve the air flow in the left cabinet 1 the effect of convection heat transfer.
  • the control module sends a signal to the control switch to first turn on the switches of the coils of the second electromagnets 7 on the left and right cabinet 1, and then turn on the first electromagnetic on the right cabinet 1.
  • the control module sends a control command to reduce the rotation speed to the right fan 3 in the right cabinet 1 .
  • the rotation speed of the right fan 3 in the right cabinet 1 will be reduced, so that the air flow entering from the air inlet 6 below the fan 3 will be reduced, so as to realize the shunting of the intake air and effectively improve the air flow in the right cabinet 1 the effect of convection heat transfer.
  • the digital video production method based on Internet big data in this solution is not limited to the content disclosed in the specific implementation manner.
  • the technical solutions in the embodiments can be extended based on the understanding of those skilled in the art. Simple alternatives made by common sense are also within the scope of this scheme.

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  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
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Abstract

本申请涉及视频制作技术领域，具体公开了一种基于互联网大数据的数字视频制作系统，包括服务器，所述服务器包括数据搜索采集模块、素材数据库、素材分类管理模块和视频生成模块，素材分类管理模块包括素材主题分类模块、素材特征分析模块，素材主题分类模块包括多个主题分类素材数据库，素材特征分析模块包括多个特征分类素材数据库，视频生成模块包括素材随机排序模块、视频数据库。本申请采用智能化系统自动生成定制的视频，具有自动化程度高以及便于操作的特点。

Description

基于互联网大数据的数字视频制作系统 技术领域
本申请涉及视频制作技术领域，具体涉及一种基于互联网大数据的智能化自动生成视频的数字视频制作系统。
背景技术
目前，数字视频的制作过程通常采用专业性很强的专业人员的偏重人工处理的过程，视频制作的自动化程度低，专业化程度高，在编辑制作影视节目时需要查找影视素材，之后用手工编辑制作，这样完成一个视频制作往往需要几天甚至十几天，不仅耗时耗力，效率低下，而且成本高昂。而采用抠像合成视频的虚拟演播室系统的智能自动化程度也不高，只适合电视台专业制作节目时应用。
发明内容
本申请意在提供一种基于互联网大数据的数字视频制作系统，采用智能化系统自动生成定制的视频，解决了现有方案自动化程度低以及专业门槛高的问题。
本申请中的基于互联网大数据的数字视频制作系统，包括服务器，所述服务器包括数据搜索采集模块、素材数据库、素材分类管理模块和视频生成模块；
所述数据搜索采集模块用于将从互联网采集的素材输入存储在素材数据库；
所述素材分类管理模块用于调用素材数据库的数据信息进行分类整理；
所述视频生成模块用于调用所述素材分类管理模块分类后的数据信息进行视频制作。
进一步，所述素材分类管理模块包括素材主题分类模块和素材特征 分析模块；
所述素材主题分类模块包括多个主题分类素材数据库，素材主题分类模块根据设定的主题类型将素材数据库的数据信息归类存入多个主题分类素材数据库；
所述素材特征分析模块包括多个特征分类素材数据库，素材特征分析模块根据设定的特征类型将主题分类素材数据库的数据信息赋值后归类存入多个特征分类素材数据库。
进一步，所述视频生成模块包括素材随机排序模块和视频数据库，所述素材随机排序模块用于根据设定的算法将获取的特征分类素材数据库的数据信息进行随机排序拼接生成视频信息存入视频数据库。
进一步，所述素材数据库包括背景素材数据库和主体素材数据库；
根据本申请的一些实施例，所述主题分类素材数据库包括背景主题分类素材数据库和主体主题分类素材数据库。
根据本申请的一些实施例，所述特征分类素材数据库包括背景特征分类素材数据库和主体特征分类素材数据库。
根据本申请的一些实施例，所述视频生成模块还包括视频抠像合成模块，所述视频抠像合成模块用于将素材随机排序模块生成的背景视频信息和主体视频信息进行抠像合成处理生成合成视频信息存入视频数据库。
根据本申请的一些实施例，，所述数字视频制作系统还包括用于为视频加入字幕的字幕生成模块。
进一步，所述字幕生成模块包括外部编辑模块、字幕导入模块和字幕信息数据库；
所述外部编辑模块用于通过数据上传端口将字幕数据信息输入存储到字幕信息数据库；
所述字幕导入模块用于调取字幕信息数据库的数据信息导入合成视频生成字幕合成视频存入视频数据库。
本申请采用智能化系统自动生成定制的视频，与现有技术相比具有如下特点：
⑴采用特征化技术，对视频素材进行特征描述，建立特征数据库；
⑵使数字视频制作由专业化向大众化发展成为可能，用户可以轻松自如的制作视频；
⑶素材来源于互联网大数据，取材范围广，数据信息全，表现形式多样化；⑷智能自动合成视频，灵活高效、实用性强，极大的提高制作效率，使视频节目制作更加丰富多彩。
综上所述，本申请中的基于互联网大数据的数字视频制作系统具有自动化程度高和便于操作的特点。
附图说明
图1是本申请实施例一中的基于互联网大数据的数字视频制作系统的示意性框图。
图2是本申请实施例二中机柜的结构示意图。
具体实施方式
实施例一
本实施例中的基于互联网大数据的数字视频制作系统基本如图1所示，包括了接入互联网的服务器，服务器包括数据搜索采集模块、素材数据库、素材分类管理模块、视频生成模块，素材分类管理模块包括素材主题分类模块、素材特征分析模块，素材主题分类模块包括多个主题分类素材数据库，素材特征分析模块包括多个特征分类素材数据库，视频生成模块包括素材随机排序模块、视频数据库。
数据搜索采集模块将从互联网采集的素材输入存储在素材数据库，数据搜索采集模块可以根据关键词搜索或其他设定的搜索条件、算法在互联网平台上搜索下载相关的数据信息，经初步筛选后输入系统。素材分类管理模块调用素材数据库的数据信息进行分类整理。素材主题分类模块根据设定的主题类型将素材数据库的数据信息归类存入多个主题分类素材数据库。素材特征分析模块根据设定的特征类型将主题分类素材数据库的数据信息赋值后归类存入多个特征分类素材数据库。视频生成模块调用特征分类素材数据库的数据信息进行视频制作。素材随机排序模块根据设定的算法将获取的特征分类素材数据库的数据信息进行 随机排序拼接生成视频信息存入视频数据库。上述方案采用智能化系统自动生成定制的视频，根据主题、特征分类标记素材按照设定的算法生成定制的视频，操作专业门槛低，自动化程度高。
为了实现视频的定制目的，使得视频呈现出层次感以及衬托环境，本方案中的素材数据库包括背景素材数据库、主体素材数据库。主题分类素材数据库包括背景主题分类素材数据库、主体主题分类素材数据库。特征分类素材数据库包括背景特征分类素材数据库、主体特征分类素材数据库。视频生成模块还包括视频抠像合成模块，视频抠像合成模块将素材随机排序模块生成的背景视频信息、主体视频信息进行抠像合成处理生成合成视频信息存入视频数据库。进一步，本方案中的数字视频制作系统还包括字幕生成模块，字幕生成模块包括字幕导入模块、字幕信息数据库，外部编辑模块通过数据上传端口将字幕数据信息输入存储在字幕信息数据库，字幕导入模块调取字幕信息数据库的数据信息导入合成视频生成字幕合成视频存入视频数据库。
本实施例中的基于互联网大数据的数字视频制作系统，适合非专业人员应用，具有灵活多样的实用的特征素材数据库，使视频制作具有智能性和自动化特征。本系统对存放于计算机的各类存贮介质中的数字化视频素材进行特征化描述，特征是指描述景观及景观中景物的各类特点、特征、状态等，景物特征可以是外形尺寸、数量、布局、色彩、新旧、运动状态、环境温度、明暗、颜色、季节、时间等，特征的程度可以采用数字标记，也可用文字标记。视频生成模块进行特征适配操作和主题限定，智能自动制作出视频节目，通过设定系统的算法，可以输出不同的结果。
例如，视频的定制内容是采用10年前北京天安门的背景重现角色的活动场面，则只要把此要求输入系统进行主题匹配和特征适配，自动制作出一个符合其要求的背景模板，通过影像合成技术将角色置入场景画面，即可制作出令用户满意的定制视频。而且，基于其选材的随机性，每次制作出的视频各不相同，但都符合算法逻辑，例如背景视频可以是从左到右旋转展示天安门的景观，也可以是从右到左旋转展示，从而给用户不同的服务体验。因此，本方案具有以下特点：⑴采用特征化技术， 对视频素材进行特征描述，建立特征数据库；⑵使数字视频制作由专业化向大众化发展成为可能，用户可以轻松自如的制作视频；⑶素材来源于互联网大数据，取材范围广，数据信息全，表现形式多样化；⑷智能自动合成视频，灵活高效、实用性强，极大的提高制作效率，使视频节目制作更加丰富多彩。
实施例二
说明书附图2中的附图标记包括，机柜1、出气口2、风扇3、弹簧4、第一电磁铁5、进气口6、第二电磁铁7、门板8。
与实施例一不同之处仅在于，本实施例中，为了提高处理能力，以应对数字视频制作这一类对于处理能力要求较高的任务，服务器采用了多个刀片式服务器，被至于如附图2所示的机柜1内，机柜1还包括出气口2、风扇3、弹簧4、第一电磁铁5、进气口6、第二电磁铁7和门板8。
如附图2所示，本实施例中的机柜1共有两个，且左右镜像对称，机柜1里面的空间分为4层，每层放置有2台设备(附图2中未画出机柜1里的空间结构与放置的设备)。本实施例中以左边的机柜1的结构进行阐述，右边的机柜1的结构与左边的机柜1的结构类似，本实施例中不再赘述。
刀片式服务器常常会遇到温度过高的问题，特别是在服务器超频状态下工作的时候，需要妥善处理散热问题。服务器超频就需要提高CPU的工作电压，工作电压升高就会引起功耗加大，从而引起发热量自然增加。一旦发热量与散热量趋于平衡，CPU温度就不再升高，发热量由CPU的功率决定，而功率又和电压成正比。此外，环境温度和风扇质量、主机环境也对散热效果有很大的影响。可见，极有可能出现左、右边的机柜1中设备的发热量不同的情况。机柜1为长方体形状，在机柜1的顶部开设有出气口2，在机柜1的底部开设有两个进气口6。机柜1的底部还安装有两个风扇3，风扇3相对于机柜1的竖直对称线对称。风扇3的具体安装方式为，风扇3由金属材料制成，风扇3通过两根弹簧4固定在机柜1的底面，弹簧4一端焊接在风扇3上，另一端焊接在机柜1的底部，风扇3位于进气口6的正上方。第一电磁铁5包括铁芯 和线圈，线圈由导电材质制成，缠绕在铁芯上，第一电磁铁5安装在支撑风扇3的右边的那根弹簧4的左边，具体方式为铁芯焊接在机柜1的底部。在机柜1的右侧，设有门板8，门板8铰接在机柜1上。第二电磁铁7包括铁芯和线圈，线圈由导电材质制成，缠绕在铁芯上，铁芯焊接在门板8上。本实施例中，出气口2处还安装有温度传感器，用来采集出气口2处的气流的温度数值；第一磁铁5、第二磁铁7的线圈的通电、断开状态，均由控制模块通过控制开关进行控制，具体的控制开关可参考现有技术。初始时，左、右两边的机柜1的门板8均处于关闭状态，出气口2、进气口6以及风扇3均处于开启状态。左、右边的机柜1上出气口2处的温度传感器实时检测出气口2处气流的温度值，并将检测出的温度数值发送到判断模块。判断模块判断左、右边的机柜1出气口2处气流的温度值的大小：若左边的、右边的机柜1出气口2处气流的温度值大小相等，说明左、右边的机柜1中的风扇3的散热效果基本相同，故不需要额外的操作。若右边的机柜1出气口2处气流的温度值大于左边的机柜1出气口2处气流的温度值，说明右边的机柜1中的风扇3的散热效果差一些，使得出气口2处的气流温度较高，这时控制模块发送信号到控制开关，先接通左边的、右边的机柜1上的第二电磁铁7的线圈的开关，然后接通左边的机柜1上的第一电磁铁5的线圈的开关。这样，左边的、右边的机柜1的门板8在第二电磁铁7的相互吸引的作用下会相互靠近，使得门板8处于打开状态；左边的机柜1的风扇3会在第一电磁铁5的吸引力作用下，向右边进行偏转。左边的机柜1的风扇3吹出的气流的一部分就会进入到右边的机柜1，帮助右边的机柜1进行散热，从而提高整体的散热效果。接着，控制模块发送降低转速的控制指令到左边的机柜1中的左边的风扇3。这样，左边的机柜1中的左边的风扇3的转速会降低，使得从该风扇3下方的进气口6进入的气流量减小，从而实现进气的分流，有效地提高左边的机柜1中的对流换热的效果。类似地，若左边的机柜1出气口2处气流的温度值大于右边的机柜1出气口2处气流的温度值，说明左边的机柜1中的风扇3的散热效果差一些，使得出气口2处的气流温度较高，这时控制模块发送信号到控制开关，先接通左边的、右边的机柜1上的第二电磁铁7 的线圈的开关，然后接通右边的机柜1上的第一电磁铁5的线圈的开关。这样，左边的、右边的机柜1的门板8在第二电磁铁7的相互吸引的作用下会相互靠近，使得门板8处于打开状态；右边的机柜1的风扇3会在第一电磁铁5的吸引力作用下，向左边进行偏转。右边的机柜1的风扇3吹出的气流的一部分就会进入到左边的机柜1，帮助左边的机柜1进行散热，从而提高整体的散热效果。接着，控制模块发送降低转速的控制指令到右边的机柜1中的右边的风扇3。这样，右边的机柜1中的右边的风扇3的转速会降低，使得从该风扇3下方的进气口6进入的气流量减小，从而实现进气的分流，有效地提高右边的机柜1中的对流换热的效果。
本方案的基于互联网大数据的数字视频制作方法并不限于具体实施方式中公开的内容，实施例中出现的技术方案可以基于本领域技术人员的理解而延伸，本领域技术人员根据本方案结合公知常识作出的简单替换方案也属于本方案的范围。

Claims (9)

  1. 基于互联网大数据的数字视频制作系统，包括服务器，其中，所述服务器包括数据搜索采集模块、素材数据库、素材分类管理模块和视频生成模块；
    所述数据搜索采集模块用于将从互联网采集的素材输入存储在素材数据库；
    所述素材分类管理模块用于调用素材数据库的数据信息进行分类整理；
    所述视频生成模块用于调用所述素材分类管理模块分类后的数据信息进行视频制作。
  2. 如权利要求1所述的基于互联网大数据的数字视频制作系统，其中，所述素材分类管理模块包括素材主题分类模块和素材特征分析模块；
    所述素材主题分类模块包括多个主题分类素材数据库，素材主题分类模块根据设定的主题类型将素材数据库的数据信息归类存入多个主题分类素材数据库；
    所述素材特征分析模块包括多个特征分类素材数据库，素材特征分析模块根据设定的特征类型将主题分类素材数据库的数据信息赋值后归类存入多个特征分类素材数据库。
  3. 如权利要求2所述的基于互联网大数据的数字视频制作系统，其中，所述视频生成模块包括素材随机排序模块和视频数据库，所述素材随机排序模块用于根据设定的算法将获取的特征分类素材数据库的数据信息进行随机排序拼接生成视频信息存入视频数据库。
  4. 如权利要求1所述的基于互联网大数据的数字视频制作系统，其中，所述素材数据库包括背景素材数据库和主体素材数据库。
  5. 如权利要求2所述的基于互联网大数据的数字视频制作系统，其中，所述主题分类素材数据库包括背景主题分类素材数据库和主体 主题分类素材数据库。
  6. 如权利要求2所述的基于互联网大数据的数字视频制作系统，其中，所述特征分类素材数据库包括背景特征分类素材数据库和主体特征分类素材数据库。
  7. 如权利要求3所述的基于互联网大数据的数字视频制作系统，其中，所述视频生成模块还包括视频抠像合成模块；所述视频抠像合成模块用于将素材随机排序模块生成的背景视频信息和主体视频信息进行抠像合成处理生成合成视频信息存入视频数据库。
  8. 如权利要求3所述的基于互联网大数据的数字视频制作系统，其中，还包括用于为视频加入字幕的字幕生成模块。
  9. 如权利要求8所述的基于互联网大数据的数字视频制作系统，其中，所述字幕生成模块包括外部编辑模块、字幕导入模块和字幕信息数据库；
    所述外部编辑模块用于通过数据上传端口将字幕数据信息输入存储到字幕信息数据库；
    所述字幕导入模块用于调取字幕信息数据库的数据信息导入合成视频生成字幕合成视频存入视频数据库。
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