CN110996124A - Original video determination method and related equipment - Google Patents
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Abstract
The application discloses an original video determining method and related equipment, and relates to an artificial intelligence technology in the technical field of computers. The specific implementation scheme is as follows: generating a video list comprising uploaded videos, wherein the video list further comprises at least one video matched with the uploaded videos; acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos. Therefore, the matched videos in the video list are scored through the video information and the author information, and the original videos in the video list are determined based on the scores of the videos, so that the efficiency and the accuracy of small video original judgment can be improved.
Description
Technical Field
The present application relates to artificial intelligence technology in the field of computer technology, and in particular, to a method and related device for determining an original video.
Background
In the small video industry, in order to obtain exposure opportunities or obtain more profit sharing, some users carry videos of other originators, and occupy the exposure traffic of the videos of the originators, so that the creation enthusiasm of the originators is reduced, and therefore, the small video originality judgment is important for protecting the benefits of the originators and the continuous development of the small video industry. However, the existing small video originality determination is usually realized in an identification processing mode that an auditor manually checks and checks one by one, so that the efficiency of small video originality determination is low.
Therefore, the problem of low efficiency exists in the existing small video original judgment.
Disclosure of Invention
The embodiment of the application provides an original video determining method and related equipment, and aims to solve the problem of low efficiency in the existing small video original judgment.
In order to solve the above technical problem, the present application is implemented as follows:
a first aspect of the present application provides a method for determining an original video, including:
generating a video list comprising uploaded videos, wherein the video list further comprises at least one video matched with the uploaded videos;
acquiring video information and author information of each video in the video list;
generating a score for each video in the video list based on the video information and author information;
based on the score of each video in the list of videos, an original video is determined in the list of videos.
Optionally, the determining an original video in the video list based on the score of each video in the video list includes:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
Optionally, the generating a score of each video in the video list based on the video information and the author information includes:
acquiring a first score value corresponding to video information of a third video and a second score value corresponding to author information of the third video, wherein the third video is any one of videos in the video list;
determining a sum of the first score value and the second score value as a score of the third video.
Optionally, in the case that the uploaded video is received, generating a video list including the uploaded video includes:
under the condition that an uploading video is received, extracting video characteristic data of the uploading video;
forming the video characteristic data of the uploaded video into a video fingerprint of the uploaded video; and under the condition that videos with video fingerprints identical to the video fingerprints of the uploaded videos exist, generating a video list comprising the uploaded videos and the videos identical to the uploaded videos.
Optionally, after determining an original video in the video list based on the score of each video in the video list, the method further includes:
and when the video in the video list is changed or the author information of the video in the video list is changed, re-executing: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos.
The second aspect of the present application also provides an original video determination device, including:
the device comprises a video list generation module, a video selection module and a video selection module, wherein the video list generation module is used for generating a video list comprising uploaded videos, and the video list further comprises at least one video matched with the uploaded videos;
the information acquisition module is used for acquiring video information and author information of each video in the video list;
the score generation module is used for generating a score of each video in the video list based on the video information and the author information;
and the original video determining module is used for determining an original video in the video list based on the grade of each video in the video list.
Optionally, the original video determining module is specifically configured to:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
Optionally, the method includes:
the scoring unit is used for acquiring a first scoring value corresponding to video information of a third video and a second scoring value corresponding to author information of the third video, wherein the third video is any one of the videos in the video list;
a determination unit configured to determine a sum of the first score value and the second score value as a score of the third video.
Optionally, the video list generating module includes:
the feature data extraction unit is used for extracting video feature data of the uploaded video under the condition that the uploaded video is received;
the video fingerprint composition unit is used for composing the video characteristic data of the uploaded video into the video fingerprint of the uploaded video;
a video list generation unit configured to generate a video list including the uploaded video and a video identical to the uploaded video, when there is a video having a video fingerprint identical to a video fingerprint of the uploaded video.
Optionally, the apparatus further comprises:
an iteration module, configured to, when a video in the video list changes or author information of a video in the video list changes, re-execute: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos.
A third aspect of the present application provides a server comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
A fourth aspect of the present application provides a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of the first aspect described above.
One embodiment in the above application has the following advantages or benefits: generating a video list comprising uploaded videos, wherein the video list further comprises at least one video matched with the uploaded videos; acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos. Because the technical means of scoring the matched videos in the video list through the video information and the author information and determining the original videos in the video list based on the scores of the videos are adopted, the technical problem of low efficiency in small video original judgment is solved, and the technical effects of efficiency and accuracy of small video original judgment are further improved.
In addition, videos matched with the uploaded videos are searched through the video fingerprints, and a video list is generated, so that the efficiency and the accuracy of searching the videos matched with the uploaded videos in the database by the server can be improved.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present application;
FIG. 2 is one of the schematic diagrams according to a second embodiment of the present application;
FIG. 3 is a second schematic diagram according to a second embodiment of the present application;
FIG. 4 is a third schematic diagram according to a second embodiment of the present application;
FIG. 5 is a fourth schematic view in accordance with a second embodiment of the present application;
fig. 6 is a block diagram of a server for implementing the inventive video determination method of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Referring to fig. 1, an original video determination method provided in an embodiment of the present application is shown in fig. 1, and the original video determination method includes the following steps:
In this embodiment, the server may generate a video list including the upload video and at least one video matching the upload video, when receiving the upload video sent by the user terminal.
The generating of the video list including the uploaded video may be that when the server receives the uploaded video, the server searches whether at least one video matching the uploaded video exists in a database of the server, and if at least one video matching the uploaded video exists in the database, a video list is made, and the video list is composed of the uploaded video and the at least one video; of course, if there is no video matching the uploaded video in the database, it may be determined that the uploaded video is the original video.
In addition, the server searches whether at least one video matching the uploaded video exists in the database thereof, and may be that the server extracts video feature data (including at least one of MD5 information, frame image data, audio data, and the like) of the uploaded video and video feature data of videos in the database, calculates similarity between the video feature data of the uploaded video and the video feature data of the videos in the database, and determines a video, of which the similarity between the video feature data and the video feature data of the uploaded video is higher than a preset similarity threshold (for example, 70% and the like), as a video matching the uploaded video.
In some embodiments, the generating, in a case that the upload video is received, a video list including the upload video includes:
under the condition that an uploading video is received, extracting video characteristic data of the uploading video;
forming the video characteristic data of the uploaded video into a video fingerprint of the uploaded video;
and under the condition that videos with video fingerprints identical to the video fingerprints of the uploaded videos exist, generating a video list comprising the uploaded videos and the videos identical to the uploaded videos.
The server can form the video fingerprints of the uploaded videos through the video characteristic data, and generates a video list from the videos with the same video fingerprints as the video fingerprints of the uploaded video in the database, so that the efficiency and accuracy of searching the videos matched with the uploaded videos in the database by the server can be improved.
And 102, acquiring video information and author information of each video in the video list.
In this embodiment, after the video list including the uploaded video and the at least one video is generated in step 101, the server may obtain video information and author information of each video in the video list.
The video information may include factors such as the video source information and the deletion information.
Here, the uploaded video may be a video that is shot by a user through a camera of the user terminal and is directly uploaded, or may also be a video that is selected and uploaded by the user from videos stored in the user terminal, so the video source information may be first indication information for indicating that the video is a shot video, or second indication information for indicating that the video is a stored video; the deletion information is used to indicate whether or not the video in the video list is deleted in the history originality determination, that is, determined as a non-original video.
In addition, the author information may be information previously entered in the server, and specifically, the author information may be information that the server sends an author authentication link to the user terminal, the user terminal displays an authentication interface when receiving a click of the authentication link by the user, the user terminal sends authentication information input by the user in the authentication interface to the server, the server marks the author information based on the authentication information to generate author information of the user, and the author information may include factors such as whether the author is a good author, a rating in the case of a good author, and whether there is a history deletion video, and the author information is stored when the author information is generated.
For example, in the case of receiving identity information uploaded by an author, an auditor at the service end may mark the author as a good-quality author and assign a grade to the author according to the uploaded identity information.
Certainly, the mark of each factor in the author information may also be updated according to the situation of the author uploading videos later, for example, when the videos uploaded by the author for many times are all non-original videos, the grade of the high-quality author of the author may be reduced or the author may be marked as a non-high-quality author and the author may be marked with a history deletion video; and in the case that the videos uploaded by the author are original videos, the author information of the author can be marked as a high-quality author by a non-high-quality author or the grade of the high-quality author of the author can be improved, and the like.
And 103, generating a score of each video in the video list based on the video information and the author information.
In this embodiment, in the case that the video information and the author information of each video are acquired in step 102, the server may generate a score of each video based on the video information and the author information of each video.
The generating of the score of the video based on the video information and the author information may be that the server scores each video according to a preset scoring rule.
Specifically, the step 103 includes: acquiring a first score value corresponding to video information of a third video and a second score value corresponding to author information of the third video, wherein the third video is any one of videos in the video list; and determining the sum of the first scoring value and the second scoring value as the score of the third video, so that the score of each video can be accurately obtained.
The first score value corresponding to the video information of the third video may be a score value of each factor (such as video source information or deletion information) in the video information preset in the server under different conditions, and is determined as the first score value according to a condition to which the factor in the video information of the third video belongs.
For example, the server presets video source information as a score of uploading video of a1 and a score of shooting video of a 2; if the deletion information is a history undeleted score of B1 and a history deleted score of B2, the server determines that the sum of a2 and B1 is the first score value when the video source of the video information is a captured video and the deletion information is a history undeleted score.
In addition, the obtaining of the second score value corresponding to the author information of the third video may be that the server obtains the author information of the third video, determines a flag of at least one factor (which may include whether the factor is a good-quality author, a rating in the case of a good-quality author, whether there is a history of deleting a video, and the like) in the author information of the third video, determines the score of each factor according to the flag of each factor in the author information of the third video, and determines the scores of all factors in the author information as the second score value.
For example, the server is preset with the score of a high-quality author of C1 and the score of a non-high-quality author of C2; a rating of D1 for a good author rating of 1, D2 for a rating of 2, and D3 for a rating of 3; the rating of the video without the history deletion is E1 and the rating of the video with the history deletion is E2, and in the case where the author information of the third video is marked as a high-quality author, the rating of the high-quality author is 3, and the video with the history deletion, the author information of the third video is the sum of C1, D3, and E2.
And step 104, determining original videos in the video list based on the scores of all the videos in the video list.
In this embodiment, after generating the score of each video in the video list in step 103, the server may determine that one video is the original video in all videos in the video list based on the score of each video.
Specifically, the step 104 may include:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
Here, the server may determine the original video in the video list according to the scores and the uploading time of each video in the video list, so that the accuracy of determining the original video by the server is improved.
In this embodiment, the steps 102 to 104 may occur in the case of uploading a video; alternatively, the video list may be executed when a video in the video list is changed or when author information of one or more videos is changed.
Specifically, after the step 102, the method may further include: and when the video in the video list is changed or the author information of the video in the video list is changed, re-executing: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the video list, the original video is determined in the video list, i.e. the above steps 102 to 104 are performed again.
Here, in the case that the video in the video list is changed or the author information is changed, the server may re-acquire the video information and the author information of the video in the video list, score the video in the video list based on the newly acquired video information and the author information, and re-determine the original video in the video list based on the new score, which may implement timely iteration of a determination result of the original video, so that the determination of the original video is more accurate.
For example, when the server receives an uploaded video which is newly uploaded by a user and is matched with a video list, the server adds the newly uploaded video into the video list, scores the video in the updated video list and judges the original video; or when the author information of a certain video in the video list is marked as not being a good author by a good author, the server re-scores each video in the video list and judges the original video based on the video information and the changed author information, and the like.
In the embodiment of the application, under the condition that the uploaded video is received, a video list comprising the uploaded video is generated, wherein the video list further comprises at least one video matched with the uploaded video; acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos. Therefore, the matched videos in the video list are scored through the video information and the author information, and the original videos in the video list are determined based on the scores of the videos, so that the efficiency and the accuracy of small video original judgment can be improved.
Referring to fig. 2, an original video determination apparatus 200 according to an embodiment of the present application includes, as shown in fig. 2:
a video list generating module 201, configured to generate a video list including an uploaded video, where the video list further includes at least one video matching the uploaded video;
an information obtaining module 202, configured to obtain video information and author information of each video in the video list;
a score generation module 203, configured to generate a score for each video in the video list based on the video information and the author information;
an original video determining module 204, configured to determine an original video in the video list based on the score of each video in the video list.
Optionally, the original video determining module 204 is specifically configured to:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
Optionally, as shown in fig. 3, the score generating module 203 includes:
the scoring unit 2031 is configured to obtain a first score value corresponding to video information of a third video and a second score value corresponding to author information of the third video, where the third video is any one of the videos in the video list;
a determining unit 2032 configured to determine the sum of the first score value and the second score value as the score of the third video.
Optionally, as shown in fig. 4, the video list generating module 201 includes:
the feature data extraction unit 2011 is configured to extract video feature data of the uploaded video when the uploaded video is received;
a video fingerprint composing unit 2012, configured to compose the video feature data of the uploaded video into a video fingerprint of the uploaded video;
a video list generating unit 2013, configured to generate a video list including the uploaded video and a video identical to the uploaded video if there is a video having a video fingerprint identical to a video fingerprint of the uploaded video.
Optionally, as shown in fig. 5, the apparatus 200 further includes:
an iteration module 205, configured to, when a video in the video list changes or author information of a video in the video list changes, re-perform: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos.
It should be noted that the original video determination apparatus 200 can implement each process implemented by the server in the embodiment of the method in fig. 1 of the present invention, and achieve the same beneficial effects, and for avoiding repetition, details are not described here again.
According to an embodiment of the present application, a server and a readable storage medium are also provided.
Fig. 6 is a block diagram of a server of an original video determination method (the original video determination method shown in fig. 1) according to an embodiment of the present application. Server is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The server may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 6, the server includes: one or more processors 601, memory 602, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executed within the server, including instructions stored in or on the memory to display graphical information of the GUI on an external input/output device (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple servers may be connected, with each device providing portions of the necessary operations (e.g., as an array of servers, a group of blade servers, or a multi-processor system). In fig. 6, one processor 601 is taken as an example.
The memory 602 is a non-transitory computer readable storage medium as provided herein. Wherein the memory stores instructions executable by at least one processor to cause the at least one processor to perform the inventive video determination methods provided herein. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to execute the original video determination method provided by the present application (the original video determination method shown in fig. 1).
The memory 602, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the original video determination method in the embodiment of the present application (for example, the video list generation module 201, the information acquisition module 202, the score generation module 203, and the original video determination module 204 shown in fig. 2). The processor 601 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 602, namely, implementing the original video determination method in the method embodiment shown in fig. 1 described above.
The memory 602 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the server processed by the applet, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 602 optionally includes memory located remotely from the processor 601, and these remote memories may be connected to an applet processing server over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The server of the original video determination method may further include: an input device 603 and an output device 604. The processor 601, the memory 602, the input device 603 and the output device 604 may be connected by a bus or other means, and fig. 6 illustrates the connection by a bus as an example.
The input device 603 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the servlet processed by the applet, such as a touch screen, keypad, mouse, track pad, touch pad, pointer stick, one or more mouse buttons, track ball, joystick, etc. The output devices 604 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
According to the technical scheme of the embodiment of the application, a video list comprising uploaded videos is generated, wherein the video list further comprises at least one video matched with the uploaded videos; acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos. Therefore, the matched videos in the video list are scored through the video information and the author information, and the original videos in the video list are determined based on the scores of the videos, so that the efficiency and the accuracy of small video original judgment can be improved.
In addition, videos matched with the uploaded videos are searched through the video fingerprints, and a video list is generated, so that the efficiency and the accuracy of searching the videos matched with the uploaded videos in the database by the server can be improved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (12)
1. An original video determination method, comprising:
generating a video list comprising uploaded videos, wherein the video list further comprises at least one video matched with the uploaded videos;
acquiring video information and author information of each video in the video list;
generating a score for each video in the video list based on the video information and author information;
based on the score of each video in the list of videos, an original video is determined in the list of videos.
2. The method of claim 1, wherein the determining an original video in the video list based on the score of each video in the video list comprises:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
3. The method of claim 1, wherein generating a score for each video in the list of videos based on the video information and author information comprises:
acquiring a first score value corresponding to video information of a third video and a second score value corresponding to author information of the third video, wherein the third video is any one of videos in the video list;
determining a sum of the first score value and the second score value as a score of the third video.
4. The method according to any one of claims 1 to 3, wherein, in case of receiving the uploaded video, generating a video list comprising the uploaded video comprises:
under the condition that an uploading video is received, extracting video characteristic data of the uploading video;
forming the video characteristic data of the uploaded video into a video fingerprint of the uploaded video;
and under the condition that videos with video fingerprints identical to the video fingerprints of the uploaded videos exist, generating a video list comprising the uploaded videos and the videos identical to the uploaded videos.
5. The method of any of claims 1-3, wherein after determining an original video in the list of videos based on the score of each video in the list of videos, further comprising:
and when the video in the video list is changed or the author information of the video in the video list is changed, re-executing: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos.
6. An original video determination device, comprising:
the device comprises a video list generation module, a video selection module and a video selection module, wherein the video list generation module is used for generating a video list comprising uploaded videos, and the video list further comprises at least one video matched with the uploaded videos;
the information acquisition module is used for acquiring video information and author information of each video in the video list;
the score generation module is used for generating a score of each video in the video list based on the video information and the author information;
and the original video determining module is used for determining an original video in the video list based on the grade of each video in the video list.
7. The apparatus of claim 6, wherein the original video determination module is specifically configured to:
determining that the first video is an original video if only one first video with the highest score exists in the video list; or
And determining that the video with the earliest uploading time in at least two second videos is the original video under the condition that at least two second videos with the highest scores exist in the video list.
8. The apparatus of claim 6, wherein the score generation module comprises:
the scoring unit is used for acquiring a first scoring value corresponding to video information of a third video and a second scoring value corresponding to author information of the third video, wherein the third video is any one of the videos in the video list;
a determination unit configured to determine a sum of the first score value and the second score value as a score of the third video.
9. The apparatus according to any one of claims 6 to 8, wherein the video list generation module comprises:
the feature data extraction unit is used for extracting video feature data of the uploaded video under the condition that the uploaded video is received;
the video fingerprint composition unit is used for composing the video characteristic data of the uploaded video into the video fingerprint of the uploaded video;
a video list generation unit configured to generate a video list including the uploaded video and a video identical to the uploaded video, when there is a video having a video fingerprint identical to a video fingerprint of the uploaded video.
10. The apparatus of any one of claims 6 to 8, further comprising:
an iteration module, configured to, when a video in the video list changes or author information of a video in the video list changes, re-execute: acquiring video information and author information of each video in the video list; generating a score for each video in the video list based on the video information and author information; based on the score of each video in the list of videos, an original video is determined in the list of videos.
11. A server, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111601115A (en) * | 2020-05-12 | 2020-08-28 | 腾讯科技（深圳）有限公司 | Video detection method, related device, equipment and storage medium |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2273797A1 (en) * | 2009-04-03 | 2011-01-12 | Sony Corporation | Information processing device, information processing method, and program |
| CN105373600A (en) * | 2015-10-30 | 2016-03-02 | 北京奇艺世纪科技有限公司 | Method and device for sorting video playlists |
| CN107852520A (en) * | 2015-09-14 | 2018-03-27 | 谷歌有限责任公司 | Manage the content uploaded |
| CN108197265A (en) * | 2017-12-29 | 2018-06-22 | 深圳市视维科技股份有限公司 | A kind of method and system based on short video search complete video |
| CN108464007A (en) * | 2016-04-13 | 2018-08-28 | 谷歌有限责任公司 | Video metadata correlation recommendation |
| CN108491553A (en) * | 2018-04-13 | 2018-09-04 | 郑俊杰 | A kind of open video index information bank establishes management method |
| CN108733737A (en) * | 2017-04-25 | 2018-11-02 | 合信息技术（北京）有限公司 | The method for building up and device of video library |
| CN109005382A (en) * | 2018-06-27 | 2018-12-14 | 深圳市轱辘汽车维修技术有限公司 | A kind of video acquisition management method and server |
| CN109151521A (en) * | 2018-10-15 | 2019-01-04 | 北京字节跳动网络技术有限公司 | A kind of original value-acquiring method of user, device, server and storage medium |
| CN109803158A (en) * | 2017-11-17 | 2019-05-24 | 上海全土豆文化传播有限公司 | Video broadcasting method and device |
| CN109960746A (en) * | 2019-03-14 | 2019-07-02 | 佛山市摄时度文化传播有限公司 | Video infringement method for early warning and device |
| US10362349B1 (en) * | 2016-12-13 | 2019-07-23 | Google Llc | Detecting channel similarity based on content reuse |
| CN110163061A (en) * | 2018-11-14 | 2019-08-23 | 腾讯科技（深圳）有限公司 | For extracting the method, apparatus, equipment and computer-readable medium of video finger print |
| CN110297942A (en) * | 2019-06-26 | 2019-10-01 | 广州市百果园信息技术有限公司 | A kind of video heuristic approach, device, equipment and storage medium |
| CN110489596A (en) * | 2019-07-04 | 2019-11-22 | 天脉聚源(杭州)传媒科技有限公司 | A kind of video detecting method, system, device and storage medium |
-
2019
- 2019-12-20 CN CN201911327852.0A patent/CN110996124B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2273797A1 (en) * | 2009-04-03 | 2011-01-12 | Sony Corporation | Information processing device, information processing method, and program |
| CN107852520A (en) * | 2015-09-14 | 2018-03-27 | 谷歌有限责任公司 | Manage the content uploaded |
| CN105373600A (en) * | 2015-10-30 | 2016-03-02 | 北京奇艺世纪科技有限公司 | Method and device for sorting video playlists |
| CN108464007A (en) * | 2016-04-13 | 2018-08-28 | 谷歌有限责任公司 | Video metadata correlation recommendation |
| US10362349B1 (en) * | 2016-12-13 | 2019-07-23 | Google Llc | Detecting channel similarity based on content reuse |
| CN108733737A (en) * | 2017-04-25 | 2018-11-02 | 合信息技术（北京）有限公司 | The method for building up and device of video library |
| CN109803158A (en) * | 2017-11-17 | 2019-05-24 | 上海全土豆文化传播有限公司 | Video broadcasting method and device |
| CN108197265A (en) * | 2017-12-29 | 2018-06-22 | 深圳市视维科技股份有限公司 | A kind of method and system based on short video search complete video |
| CN108491553A (en) * | 2018-04-13 | 2018-09-04 | 郑俊杰 | A kind of open video index information bank establishes management method |
| CN109005382A (en) * | 2018-06-27 | 2018-12-14 | 深圳市轱辘汽车维修技术有限公司 | A kind of video acquisition management method and server |
| CN109151521A (en) * | 2018-10-15 | 2019-01-04 | 北京字节跳动网络技术有限公司 | A kind of original value-acquiring method of user, device, server and storage medium |
| CN110163061A (en) * | 2018-11-14 | 2019-08-23 | 腾讯科技（深圳）有限公司 | For extracting the method, apparatus, equipment and computer-readable medium of video finger print |
| CN109960746A (en) * | 2019-03-14 | 2019-07-02 | 佛山市摄时度文化传播有限公司 | Video infringement method for early warning and device |
| CN110297942A (en) * | 2019-06-26 | 2019-10-01 | 广州市百果园信息技术有限公司 | A kind of video heuristic approach, device, equipment and storage medium |
| CN110489596A (en) * | 2019-07-04 | 2019-11-22 | 天脉聚源(杭州)传媒科技有限公司 | A kind of video detecting method, system, device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 庄晓梅: "《基于DCT域数字图像鲁棒水印方案的研究及实现》", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111601115A (en) * | 2020-05-12 | 2020-08-28 | 腾讯科技（深圳）有限公司 | Video detection method, related device, equipment and storage medium |
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