CN111859017A - Digital video production system based on internet big data - Google Patents
Digital video production system based on internet big data Download PDFInfo
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- CN111859017A CN111859017A CN202010706350.5A CN202010706350A CN111859017A CN 111859017 A CN111859017 A CN 111859017A CN 202010706350 A CN202010706350 A CN 202010706350A CN 111859017 A CN111859017 A CN 111859017A
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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
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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
- G06F16/71—Indexing; Data structures therefor; Storage structures
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- 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, rendering scenes according to MPEG-4 scene graphs
- H04N21/44016—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 scene graphs involving splicing one content stream with another content stream, e.g. for substituting a video clip
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- 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
Abstract
The application relates to the technical field of video production, and particularly discloses a digital video production system based on internet big data, which comprises a server, the server comprises a data search acquisition module, a material database, a material classification management module and a video generation module, the material classification management module comprises a material theme classification module and a material characteristic analysis module, the material theme classification module comprises a plurality of theme classification material databases, the material characteristic analysis module comprises a plurality of characteristic classification material databases, and the video generation module comprises a material random sequencing module and a video database. The method and the device have the advantages that the customized video is automatically generated by the intelligent system, and the automation degree is high and the operation is convenient.
Description
Technical Field
The application relates to the technical field of video production, in particular to an intelligent automatic video generation digital video production system based on internet big data.
Background
At present, the production process of digital video usually adopts a process of heavy manual treatment by professional personnel with strong specialization, the automation degree of video production is low, the specialization degree is high, video materials need to be searched when a video program is edited and produced, and then the video program is manually edited and produced, so that the production of one video often needs several days or even ten days, and the method not only consumes time and labor and has low efficiency, but also has high cost. The intelligent automation degree of the virtual studio system adopting the keying and synthesizing video is not high, and the system is only suitable for being applied when a television station professionally makes programs.
Disclosure of Invention
The application aims 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 of the existing scheme.
The digital video production system based on the internet big data comprises a server, wherein the server comprises a data searching and collecting module, a material database, a material classification management module and a video generating module;
the data searching and collecting module is used for inputting and storing the materials collected from the Internet in a material database;
the material classification management module is used for calling data information of the material database to perform classification and arrangement;
the video generation module is used for calling the data information classified by the material classification management module to make a video.
Further, the material classification management module comprises a material theme classification module and a material characteristic analysis module;
the material theme classification module comprises a plurality of theme classification material databases, and the material theme classification module classifies the data information of the material databases into the plurality of theme classification material databases according to the set theme type;
The material characteristic analysis module comprises a plurality of characteristic classification material databases, and the material characteristic analysis module assigns the data information of the theme classification material database according to the set characteristic types and then classifies and stores the data information into the plurality of characteristic classification material databases.
Further, the video generation module comprises a material random ordering module and a video database, and the material random ordering module is used for randomly ordering and splicing the acquired data information of the characteristic classification material database according to a set algorithm to generate video information and storing the video information into the video database.
Further, the material database comprises a background material database and a main body material database;
according to some embodiments of the present application, the subject classification stories database includes a background subject classification stories database and a subject classification stories database.
According to some embodiments of the present application, the feature classification story database includes a background feature classification story database and a body feature classification story database.
According to some embodiments of the present application, the video generation module further includes a video matting and synthesis module, and the video matting and synthesis module is configured to perform matting and synthesis processing on the background video information and the main body video information generated by the material random ordering module to generate synthesized video information, and store the synthesized video information in the video database.
According to some embodiments of the present application, the digital video production system further comprises a subtitle generation module for subtitling the video.
Further, the subtitle generating module comprises an external editing module, a subtitle importing module and a subtitle information database;
the external editing module is used for inputting and storing the caption data information into the caption information database through the data uploading port;
and the caption import module is used for calling data information of the caption information database, importing the data information into the synthesized video, generating a caption synthesized video and storing the caption synthesized video into the video database.
This application adopts intelligent system automatic generation customized video, compares with prior art and has following characteristics:
the method comprises the steps of performing characteristic description on video materials by adopting a characterization technology, and establishing a characteristic database;
secondly, the digital video production is possible to develop from specialization to popularization, and a user can easily and freely produce videos;
the materials are derived from internet big data, the material taking range is wide, the data information is complete, and the expression forms are diversified; the intelligent automatic synthesis video is flexible, efficient and high in practicability, and the manufacturing efficiency is greatly improved, so that the video program is more colorful.
In summary, the digital video production system based on the internet big data in the application has the characteristics of high automation degree and convenient operation.
Drawings
Fig. 1 is a schematic block diagram of an internet big data based digital video production system according to a first embodiment of the present application.
Fig. 2 is a schematic structural diagram of a cabinet in the second embodiment of the present application.
Detailed Description
Example one
The digital video production system based on the internet big data in the embodiment is basically as shown in fig. 1, and comprises a server accessed to the internet, wherein the server comprises a data search acquisition module, a material database, a material classification management module and a video generation module, the material classification management module comprises a material theme classification module and a material characteristic analysis module, the material theme classification module comprises a plurality of theme classification material databases, the material characteristic analysis module comprises a plurality of characteristic classification material databases, and the video generation module comprises a material random sequencing module and a video database.
The data searching and collecting module inputs and stores the materials collected from the internet in a material database, and the data searching and collecting module can search and download related data information on an internet platform according to keyword searching or other set searching conditions and algorithms, and inputs the data information into the system after preliminary screening. And the material classification management module calls the data information of the material database to classify and sort. And the material theme classification module classifies the data information of the material database into a plurality of theme classification material databases according to the set theme type. And the material characteristic analysis module assigns the data information of the subject classification material database according to the set characteristic types and then classifies and stores the data information into a plurality of characteristic classification material databases. And the video generation module calls the data information of the characteristic classification material database to produce the video. And the material random sequencing module randomly sequences and splices the acquired data information of the characteristic classification material database according to a set algorithm to generate video information and stores the video information into the video database. According to the scheme, the customized video is automatically generated by adopting an intelligent system, the customized video is generated according to the theme and the characteristic classification marking materials and the set algorithm, the operation professional threshold is low, and the automation degree is high.
In order to realize the purpose of customizing the video and enable the video to present a layering sense and a setback environment, the material database in the scheme comprises a background material database and a main body material database. The theme classification material database comprises a background theme classification material database and a main theme classification material database. The characteristic classification material database comprises a background characteristic classification material database and a main body characteristic classification material database. The video generation module also comprises a video matting and synthesizing module, and the video matting and synthesizing module carries out matting and synthesizing processing on the background video information and the main body video information generated by the material random sequencing module to generate synthesized video information which is stored in a video database. Furthermore, the digital video production system in the scheme further comprises a caption generating module, wherein the caption generating module comprises a caption importing module and a caption information database, the external editing module inputs and stores caption data information into the caption information database through a data uploading port, and the caption importing module calls the data information of the caption information database, leads the data information into a synthesized video, generates a caption synthesized video and stores the caption synthesized video into the video database.
The digital video production system based on the internet big data in the embodiment is suitable for non-professional personnel, and has a flexible and various practical characteristic material database, so that the video production has intelligent and automatic characteristics. The system carries out characteristic description on digital video materials stored in various storage media of a computer, the characteristic refers to describing various characteristics, states and the like of scenery in the landscape and the landscape, the scenery characteristics can be appearance size, quantity, layout, color, old and new, motion state, environment temperature, brightness, color, season, time and the like, and the degree of the characteristic can be marked by numbers or words. The video generation module performs feature adaptation operation and theme limitation, intelligently and automatically generates video programs, and can output different results by setting the algorithm of the system.
The customized video satisfying the user can be manufactured by only inputting the requirements into the system to perform theme matching and feature adaptation, automatically manufacturing a background template meeting the requirements, and putting the role into a scene picture through an image synthesis technology. Moreover, based on the randomness of the selected materials, the videos manufactured each time are different and accord with the algorithm logic, so that different service experiences are provided for users. Therefore, the scheme has the following characteristics: the method comprises the steps of performing characteristic description on video materials by adopting a characterization technology, and establishing a characteristic database; secondly, the digital video production is possible from specialization to popularization, and a user can easily and freely produce videos; the materials are derived from internet big data, the material taking range is wide, the data information is complete, and the expression forms are diversified; the intelligent automatic synthesis video is flexible, efficient and high in practicability, and the manufacturing efficiency is greatly improved, so that the video program is more colorful.
Example two
The reference numbers in the attached figure 2 of the specification include a cabinet 1, 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.
The difference from the first embodiment is only that in this embodiment, in order to improve the processing capacity and cope with tasks such as digital video production which have high requirements on the processing capacity, the server employs a plurality of blade servers, and as shown in fig. 2, in the cabinet 1, 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 plate 8.
As shown in fig. 2, the number of the cabinets 1 in this embodiment is two, and the cabinets are symmetrical to each other in a mirror image manner, the space inside the cabinet 1 is divided into 4 layers, and 2 devices are placed on each layer (the space structure and the devices placed in the cabinet 1 are not shown in fig. 2). In this embodiment, the structure of the left cabinet 1 is explained, and the structure of the right cabinet 1 is similar to that of the left cabinet 1, and is not described again in this embodiment.
Blade servers often suffer from excessive temperatures, particularly when the servers are operating in an over-frequency mode, where heat dissipation needs to be properly addressed. The operating voltage of the CPU needs to be increased when the server exceeds the frequency, and the power consumption is increased when the operating voltage is increased, so that the heating value is naturally increased. Once the heat generation quantity and the heat dissipation quantity tend to be balanced, the temperature of the CPU does not rise any more, the heat generation quantity is determined by the power of the CPU, and the power is in direct proportion to the voltage. In addition, the ambient temperature, the fan quality and the host environment also have great influence on the heat dissipation effect. As can be seen, the heat generation amounts of the devices in the left and right racks 1 are likely to be different. The cabinet 1 is cuboid, the top of the cabinet 1 is provided with an air outlet 2, and the bottom of the cabinet 1 is provided with two air inlets 6. Two fans 3 are further mounted at the bottom of the cabinet 1, and the fans 3 are symmetrical relative to the vertical symmetry line of the cabinet 1. The specific installation mode of the fan 3 is that the fan 3 is made of metal materials, the fan 3 is fixed on the bottom surface of the cabinet 1 through two springs 4, one end of each spring 4 is welded on the fan 3, the other end of each spring is welded at the bottom of the cabinet 1, and the fan 3 is located right above the air inlet 6. First electro-magnet 5 includes iron core and coil, and the coil is made by electrically conductive material, and the winding is on the iron core, and first electro-magnet 5 is installed on the left side of the spring 4 that supports fan 3 on the right, and the concrete mode is the iron core welding in the bottom of rack 1. And a door plate 8 is arranged on the right side of the cabinet 1, and the door plate 8 is hinged on the cabinet 1. The second electromagnet 7 includes an iron core and a coil, the coil is made of a conductive material and wound on the iron core, and the iron core is welded on the door panel 8. In this embodiment, a temperature sensor is further installed at the air outlet 2 for collecting a temperature value of the air flow at the air outlet 2; the power-on and power-off states of the coils of the first magnet 5 and the second magnet 7 are controlled by the control module through the control switch, and the specific control switch can refer to the prior art. Initially, the door panels 8 of the cabinet 1 on the left and right sides are all in a closed state, and the air outlet 2, the air inlet 6 and the fan 3 are all in an open state. The temperature sensors at the air outlets 2 on the left and right machine cabinets 1 detect the temperature value of the air flow at the air outlets 2 in real time, and send the detected temperature value to the judgment module. The judging module judges the temperature value of the airflow at the air outlet 2 of the cabinet 1 on the left and the right sides: if the temperature values of the air flows at the air outlets 2 of the left and right cabinets 1 are equal, it is indicated that the heat dissipation effects of the fans 3 in the left and right cabinets 1 are substantially the same, and thus no additional operation is required. If the temperature value of the air flow at the air outlet 2 of the right cabinet 1 is greater than the temperature value of the air flow at the air outlet 2 of the left cabinet 1, it is indicated that the heat dissipation effect of the fan 3 in the right cabinet 1 is poor, so that the temperature of the air flow at the air outlet 2 is high, at this time, the control module sends a signal to the control switch, the switch of the coil of the second electromagnet 7 on the left cabinet 1 and the right cabinet 1 is firstly switched on, and then the switch of the coil of the first electromagnet 5 on the left cabinet 1 is switched on. Thus, the door panels 8 of the left and right cabinets 1 approach each other under the action of the attraction of the second electromagnets 7, so that the door panels 8 are in an open state; the fan 3 of the left cabinet 1 is deflected to the right by the attraction of the first electromagnet 5. A part of the airflow blown out by the fan 3 of the left cabinet 1 enters the right cabinet 1 to help the right cabinet 1 to dissipate heat, so that the overall heat dissipation effect is improved. The control module then sends a control command to reduce the rotational speed to the left fan 3 in the left cabinet 1. In this way, the rotation speed of the left fan 3 in the left cabinet 1 is reduced, so that the amount of airflow entering from the air inlet 6 below the fan 3 is reduced, thereby achieving the diversion of the inlet air and effectively improving the effect of convective heat transfer in the left cabinet 1. Similarly, if the temperature value of the air flow at the air outlet 2 of the left cabinet 1 is greater than the temperature value of the air flow at the air outlet 2 of the right cabinet 1, it is indicated that the heat dissipation effect of the fan 3 in the left cabinet 1 is poor, so that the temperature of the air flow at the air outlet 2 is high, at this time, the control module sends a signal to the control switch, the switch of the coil of the second electromagnet 7 on the left and right cabinets 1 is turned on first, and then the switch of the coil of the first electromagnet 5 on the right cabinet 1 is turned on. Thus, the door panels 8 of the left and right cabinets 1 are close to each other under the attraction of the second electromagnets 7, so that the door panels 8 are in an open state; the fan 3 of the right cabinet 1 is deflected to the left by the attraction force of the first electromagnet 5. A part of the airflow blown by the fan 3 of the right cabinet 1 enters the left cabinet 1 to help the left cabinet 1 to dissipate heat, so that the overall heat dissipation effect is improved. The control module then sends a control command to reduce the rotational speed to the right fan 3 in the right cabinet 1. Like this, the rotational speed of right fan 3 in right rack 1 can reduce for the air flow that gets into from air inlet 6 below this fan 3 reduces, thereby realizes the reposition of redundant personnel of admitting air, improves the effect of the convection heat transfer in the rack 1 on right effectively.
The method for producing digital video based on internet big data of the scheme is not limited to the content disclosed in the specific embodiment, the technical schemes presented in the embodiments can be extended based on the understanding of the person skilled in the art, and the simple alternatives made by the person skilled in the art according to the scheme and the common general knowledge also belong to the scope of the scheme.
Claims (9)
1. The digital video production system based on the internet big data comprises a server, and is characterized in that the server comprises a data search acquisition module, a material database, a material classification management module and a video generation module;
the data searching and collecting module is used for inputting and storing the materials collected from the Internet in a material database;
the material classification management module is used for calling data information of the material database to perform classification and arrangement;
the video generation module is used for calling the data information classified by the material classification management module to make a video.
2. The internet big data-based digital video production system of claim 1, wherein the material classification management module comprises a material subject classification module and a material feature analysis module;
the material theme classification module comprises a plurality of theme classification material databases, and the material theme classification module classifies the data information of the material databases into the plurality of theme classification material databases according to the set theme type;
The material characteristic analysis module comprises a plurality of characteristic classification material databases, and the material characteristic analysis module assigns the data information of the theme classification material database according to the set characteristic types and then classifies and stores the data information into the plurality of characteristic classification material databases.
3. The internet big data-based digital video production system of claim 2, wherein the video generation module comprises a material random ordering module and a video database, and the material random ordering module is configured to randomly order and splice the acquired data information of the characteristic classification material database according to a set algorithm to generate video information to be stored in the video database.
4. The internet big data-based digital video production system of claim 1, wherein the material database includes a background material database and a main body material database.
5. The internet big data-based digital video production system of claim 2, wherein the subject classification story database includes a background subject classification story database and a main subject classification story database.
6. The internet big data-based digital video production system of claim 2, wherein the feature classification materials database comprises a background feature classification materials database and a body feature classification materials database.
7. The internet big data-based digital video production system of claim 3, wherein the video generation module further comprises a video matting and synthesis module; the video keying synthesis module is used for carrying out keying synthesis processing on the background video information and the main body video information generated by the material random sequencing module to generate synthesized video information and storing the synthesized video information into the video database.
8. The internet big data-based digital video production system of claim 3, further comprising a subtitle generation module for subtitling the video.
9. The internet big data-based digital video production system of claim 8, wherein the subtitle generation module comprises an external editing module, a subtitle import module, and a subtitle information database;
the external editing module is used for inputting and storing the caption data information into a caption information database through a data uploading port;
and the caption import module is used for calling data information of the caption information database, importing the data information into the synthesized video, generating a caption synthesized video and storing the caption synthesized video into the video database.
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| CN202010706350.5A CN111859017A (en) | 2020-07-21 | 2020-07-21 | Digital video production system based on internet big data |
| PCT/CN2020/105301 WO2022016587A1 (en) | 2020-07-21 | 2020-07-28 | Internet big data-based digital video production system |
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| CN202010706350.5A CN111859017A (en) | 2020-07-21 | 2020-07-21 | Digital video production system based on internet big data |
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| CN113489919A (en) * | 2021-06-21 | 2021-10-08 | 北京德风新征程科技有限公司 | Digital video production system based on internet big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110557688A (en) * | 2018-06-04 | 2019-12-10 | 上海临境文化传播有限公司 | Digital video production method |
| CN110557653A (en) * | 2018-06-04 | 2019-12-10 | 上海临境文化传播有限公司 | Digital video production method based on internet big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| GB2508242B (en) * | 2012-11-27 | 2016-08-03 | Mirriad Advertising Ltd | Producing video data |
| CN110620882A (en) * | 2018-06-04 | 2019-12-27 | 上海临境文化传播有限公司 | Picture-in-picture digital video production method |
| CN109819179B (en) * | 2019-03-21 | 2022-02-01 | 腾讯科技（深圳）有限公司 | Video editing method and device |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110557688A (en) * | 2018-06-04 | 2019-12-10 | 上海临境文化传播有限公司 | Digital video production method |
| CN110557653A (en) * | 2018-06-04 | 2019-12-10 | 上海临境文化传播有限公司 | Digital video production method based on internet big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113489919A (en) * | 2021-06-21 | 2021-10-08 | 北京德风新征程科技有限公司 | Digital video production system based on internet big data |
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