CN113645483A - Cross-platform automatic video editing method - Google Patents
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Abstract
The invention discloses a method for automatically clipping a video in a cross-platform manner, which comprises a clipping platform system, the editing platform system comprises a front-end interaction module, a platform parameter module, a picture adjusting algorithm module, a personalized customization module, an animation special effect and sound effect library, a video cover recommendation algorithm module and a rendering synthesis technology module, recommends the most appropriate proportion through automatic video analysis, the key frame screenshot analysis is carried out on the video picture, the relationship between the characters and other objects in the picture is judged through the image analysis, the time and the labor cost are saved, firstly, the manufacturing time is greatly shortened, and secondly, the cost of hiring professionals to process the video is eliminated, the invention reduces the threshold of video production, enables excellent creators to reproduce high-quality video, improves the income, and enables the creators to exert the maximum value of the channel to the maximum extent.
Description
Technical Field
The invention relates to the technical field of cross-platform automatic video clipping methods, in particular to a cross-platform automatic video clipping method.
Background
Short video creation is a common behavior, most creators can distribute videos to multiple platforms, and due to requirements and limitations of different platforms, the videos need to be edited and output separately for different platforms after creation so as to adapt to platform requirements and achieve optimal viewing experience.
Some creators can rely on a professional operation organization MCN to solve the problem, pictures are processed through editing personnel, the platform is suitable for different platforms, but some independent creators often do not have time and energy to do the fine work and can only directly issue the pictures, so that people often see that a horizontal screen video is displayed in a vertical version interface in a tremble and video number, the upper side and the lower side of the horizontal screen video have black edges, or the left side and the right side of the vertical version video are left in good sight and watermelon video, and therefore the method for automatically editing the videos across platforms is provided.
Disclosure of Invention
The invention aims to provide a method for automatically editing videos across platforms, which aims to solve the problems in the background technology, a user can prepare, upload or import an original video into the system, the system recommends the most appropriate proportion through automatic video analysis, and the user can output the videos in batches only by individually customizing templates with different proportions.
In order to achieve the purpose, the invention provides the following technical scheme: a method for automatically clipping videos across platforms comprises a clipping platform system, wherein the clipping platform system comprises a front-end interaction module, a platform parameter module, a picture adjusting algorithm module, a personalized customization module, an animation special effect and sound effect library, a video cover recommendation algorithm module and a rendering synthesis technology module.
Preferably, the front-end interaction module includes a human-computer interaction display screen, which is a main interface for a user to perform operations, such as MCN interaction documents.
Preferably, the platform parameter module records common parameters of different platforms, such as picture scale, resolution, video coding, and the like.
Preferably, the difficulty of the image adjustment algorithm module in performing the horizontal-vertical video transformation is that the image content is cut off after the scale is adjusted, the ornamental value is reduced after the adjustment, or the image is lost in focus, the algorithm performs key frame screenshot analysis on the video image, the relationship between people and other objects in the image is judged through image analysis, if the people are people, the people are highlighted by taking the people as the center, if no people are available, the people are cut off by taking the image as the center in equal proportion, and the image adjustment algorithm is as follows:
s1: extracting each frame image of an original video to generate a PNG format video image sequence;
s2: extracting the audio of the original video to generate an original video audio file in a WAV format;
s3: respectively carrying out image processing on each frame of image to generate a binarized labeled graph, wherein the values of pixel points of figures, namely foreground pixel points, in the labeled graph are set to be 1, and the values of pixel points of non-figures, namely background pixel points, are set to be 0;
s4: extracting a pure human figure without a background based on the superposition calculation of the marked figure and the original figure;
s5: superposing the pure portrait image and the new material background image, and placing the vertical central line of the portrait image at the right side of the background image to generate a portrait image replacing the background;
s6: drawing a caption at the bottom of a portrait picture replacing a background, drawing a logo at the upper left corner of the picture to form a filmed picture with the caption, and calculating caption content drawn on the current filmed picture according to the matching of caption time and a time axis of an image sequence during caption drawing;
s7: combining and integrating the sequence of the filmed images into original video and audio in sequence to generate a filmed main video segment, a filmed introduction segment based on video titles, character information and the like, and a filmed summary segment based on the video abstract;
s8: the title, introduction clip, main video clip, total clip, end clip, background music, etc. are combined together to form a filmed video.
Preferably, the personalized customization module comprises different platforms, wherein different audiences exist, and the system provides personalized customization aiming at different channel characteristics, and the specific steps are as follows:
s1: extracting medical keywords in the doctor caption;
s2: matching with material labels in a material library based on the keywords to find corresponding keyword material pictures;
s3: drawing the keyword material pictures into a continuous animation image sequence according to frames based on animation design styles;
s4: drawing the keyword animation image sequence into each frame of image of the video to form personalized keyword animation, wherein the insertion time of the animation is consistent with the time of a subtitle sentence where the keyword is located;
s5: the style of popping up a picture-in-picture on the left side of a character is used for a single keyword appearing in a subtitle, the animation style displayed by using a multi-picture arrangement is used for a plurality of ranking keywords appearing in the subtitle, and the animation style described by a title is used for a concept explanatory keyword appearing in the subtitle.
Preferably, the video cover recommendation algorithm module contains a filtering algorithm, a cover recommended by the video is automatically generated according to the key frames, after the key frames are intercepted, each frame is not suitable for being used as a cover, unsuitable frames are removed through the filtering algorithm, and the algorithm specifically comprises the following steps:
s1: extracting a portrait of the front face of the main figure of the video;
s2: drawing the main character information into a subtitle style;
s3: drawing the video content title into a large title thickening style;
s4: the portrait, the character information, the major title and the minor title are drawn on the background picture to form a cover.
Preferably, the rendering and synthesizing technology module obtains a final piece through rendering and synthesizing, a user can obtain a plurality of videos at one time, and the system generates the piece in a mode of platform + Arabic number numbering.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, through automatic video analysis, the most suitable proportion is recommended, key frame screenshot analysis is carried out on a video picture, the relation between characters and other objects in the picture is judged through image analysis, if the characters are characters, the characters are highlighted by taking the characters as the center, if no characters are available, the characters are intercepted in equal proportion by taking the picture as the center, and a user can output the characters in batches only by performing personalized customization aiming at different proportion templates, and a cover page recommended by the video is generated automatically according to the key frame, so that the time and the labor cost are saved.
Drawings
Fig. 1 is a schematic view of the overall structure of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a method for automatically clipping videos across platforms comprises a clipping platform system, wherein the clipping platform system comprises a front-end interaction module, a platform parameter module, a picture adjusting algorithm module, a personalized customization module, an animation special effect and sound effect library, a video cover recommendation algorithm module and a rendering synthesis technology module;
the front-end interaction module comprises a man-machine interaction display screen which is a main interface for a user to operate, such as an MCN (Multi-core network) interaction document;
common parameters of different platforms, such as picture proportion, resolution, video coding and the like, are recorded in the platform parameter module;
the difficulty of the image adjusting algorithm module for video horizontal and vertical transformation is that the image content is cut off after the proportion is adjusted, the ornamental value is reduced after the adjustment, or the image is lost, the algorithm carries out key frame screenshot analysis on the video image, the relationship between people and other objects in the image is judged through image analysis, if the people are the people, the people are highlighted by taking the people as the center, if no people exist, the people are cut off by taking the image as the center in equal proportion, and the image adjusting algorithm is as follows:
s1: extracting each frame image of an original video to generate a PNG format video image sequence;
s2: extracting the audio of the original video to generate an original video audio file in a WAV format;
s3: respectively carrying out image processing on each frame of image to generate a binarized labeled graph, wherein the values of pixel points of figures, namely foreground pixel points, in the labeled graph are set to be 1, and the values of pixel points of non-figures, namely background pixel points, are set to be 0;
s4: extracting a pure human figure without a background based on the superposition calculation of the marked figure and the original figure;
s5: superposing the pure portrait image and the new material background image, and placing the vertical central line of the portrait image at the right side of the background image to generate a portrait image replacing the background;
s6: drawing a caption at the bottom of a portrait picture replacing a background, drawing a logo at the upper left corner of the picture to form a filmed picture with the caption, and calculating caption content drawn on the current filmed picture according to the matching of caption time and a time axis of an image sequence during caption drawing;
s7: combining and integrating the sequence of the filmed images into original video and audio in sequence to generate a filmed main video segment, a filmed introduction segment based on video titles, character information and the like, and a filmed summary segment based on the video abstract;
s8: combining a film head, an introduction segment, a main video segment, a total segment, a film tail, background music and the like to form a film video;
the personalized customization module comprises different platforms, wherein different audiences exist, and the system provides personalized customization aiming at different channel characteristics, and the specific steps are as follows:
s1: extracting medical keywords in the doctor caption;
s2: matching with material labels in a material library based on the keywords to find corresponding keyword material pictures;
s3: drawing the keyword material pictures into a continuous animation image sequence according to frames based on animation design styles;
s4: drawing the keyword animation image sequence into each frame of image of the video to form personalized keyword animation, wherein the insertion time of the animation is consistent with the time of a subtitle sentence where the keyword is located;
s5: using a style of popping up a picture-in-picture on the left side of a character for a single keyword appearing in a subtitle, using an animation style displayed by a multi-picture arrangement for a plurality of arranged keywords appearing in the subtitle, and using an animation style described by a title for a concept explanatory keyword appearing in the subtitle, for example, providing a one-key-three-link template for beep-li; aiming at the express hand, a family people attention template is provided; aiming at the jittering, the method has the function of automatically filling up the upper and lower blanks by the video subtitles, and can maximally enable the creators to play the maximum value of the channel;
the video cover recommendation algorithm module comprises a filtering algorithm, automatically generates a cover recommended by a video according to a key frame, after the key frame is intercepted, each frame is not suitable for being used as a cover, and unsuitable frames are removed through the filtering algorithm, wherein the algorithm comprises the following specific steps:
s1: extracting a portrait of the front face of the main figure of the video;
s2: drawing the main character information into a subtitle style;
s3: drawing the video content title into a large title thickening style;
s4: drawing a portrait, character information, a large title and a small title on a background picture to form a cover, taking a certain nethong lecture video as an example, after intercepting a key frame, removing frames of characters with closed eyes, poor expression, side body, back body, poor light and the like, intercepting an optimal screenshot from a high-quality picture, and matching characters to make a video cover;
the rendering and synthesizing technology module obtains the final piece through rendering and synthesizing, a user can obtain a plurality of videos at one time, and the system generates the piece in a mode of platform + Arabic number numbering.
According to the invention, through automatic video analysis, the most suitable proportion is recommended, key frame screenshot analysis is carried out on a video picture, and the relation between people and other objects in the picture is judged through image analysis. If the user is a character, the character is highlighted by taking the character as the center, if the user is not the character, the image is captured in equal proportion by taking the picture as the center, the user only needs to perform personalized customization aiming at different proportion templates, batch output can be realized, a cover page of video recommendation is automatically generated according to a key frame, time and labor cost are saved, firstly, the manufacturing time is greatly shortened, and secondly, the cost of engaging a professional to process the video is eliminated.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A method for automatically clipping a video across platforms, comprising: the system comprises a clipping platform system, wherein the clipping platform system comprises a front-end interaction module, a platform parameter module, a picture adjusting algorithm module, a personalized customization module, an animation special effect and sound effect library, a video cover recommendation algorithm module and a rendering synthesis technology module.
2. The method for automatically clipping video across platforms according to claim 1, wherein: the front-end interaction module comprises a man-machine interaction display screen which is a main interface for a user to operate, such as an MCN (computer-controlled network) interaction document.
3. The method for automatically clipping video across platforms according to claim 1, wherein: the platform parameter module records common parameters of different platforms, such as picture proportion, resolution, video coding and the like.
4. The method for automatically clipping video across platforms according to claim 1, wherein: the difficulty of the image adjusting algorithm module in video horizontal and vertical transformation is that the image content is cut off after the proportion is adjusted, the ornamental value is reduced after adjustment, or the image is mainly lost, the algorithm carries out key frame screenshot analysis on the video image, the relationship between people and other objects in the image is judged through image analysis, if the people are the people, the people are highlighted by taking the people as the center, if no people exist, the people are cut off by taking the image as the center in equal proportion, and the image adjusting algorithm is as follows:
s1: extracting each frame image of an original video to generate a PNG format video image sequence;
s2: extracting the audio of the original video to generate an original video audio file in a WAV format;
s3: respectively carrying out image processing on each frame of image to generate a binarized labeled graph, wherein the values of pixel points of figures, namely foreground pixel points, in the labeled graph are set to be 1, and the values of pixel points of non-figures, namely background pixel points, are set to be 0;
s4: extracting a pure human figure without a background based on the superposition calculation of the marked figure and the original figure;
s5: superposing the pure portrait image and the new material background image, and placing the vertical central line of the portrait image at the right side of the background image to generate a portrait image replacing the background;
s6: drawing a caption at the bottom of a portrait picture replacing a background, drawing a logo at the upper left corner of the picture to form a filmed picture with the caption, and calculating caption content drawn on the current filmed picture according to the matching of caption time and a time axis of an image sequence during caption drawing;
s7: combining and integrating the sequence of the filmed images into original video and audio in sequence to generate a filmed main video segment, a filmed introduction segment based on video titles, character information and the like, and a filmed summary segment based on the video abstract;
s8: the title, introduction clip, main video clip, total clip, end clip, background music, etc. are combined together to form a filmed video.
5. The method for automatically clipping video across platforms according to claim 1, wherein: the personalized customization module comprises different platforms, wherein different audiences exist, and the system provides personalized customization aiming at different channel characteristics, and the specific steps are as follows:
s1: extracting medical keywords in the doctor caption;
s2: matching with material labels in a material library based on the keywords to find corresponding keyword material pictures;
s3: drawing the keyword material pictures into a continuous animation image sequence according to frames based on animation design styles;
s4: drawing the keyword animation image sequence into each frame of image of the video to form personalized keyword animation, wherein the insertion time of the animation is consistent with the time of a subtitle sentence where the keyword is located;
s5: the style of popping up a picture-in-picture on the left side of a character is used for a single keyword appearing in a subtitle, the animation style displayed by using a multi-picture arrangement is used for a plurality of ranking keywords appearing in the subtitle, and the animation style described by a title is used for a concept explanatory keyword appearing in the subtitle.
6. The method for automatically clipping video across platforms according to claim 1, wherein: the video cover recommendation algorithm module comprises a filtering algorithm, automatically generates a cover recommended by a video according to a key frame, after the key frame is intercepted, each frame is not suitable for being used as a cover, and unsuitable frames are removed through the filtering algorithm, wherein the algorithm comprises the following specific steps:
s1: extracting a portrait of the front face of the main figure of the video;
s2: drawing the main character information into a subtitle style;
s3: drawing the video content title into a large title thickening style;
s4: the portrait, the character information, the major title and the minor title are drawn on the background picture to form a cover.
7. The method for automatically clipping video across platforms according to claim 1, wherein: the rendering and synthesizing technology module obtains the final piece through rendering and synthesizing, a user can obtain a plurality of videos at one time, and the system generates the piece in a mode of platform + Arabic number numbering.
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| CN108833971A (en) * | 2018-06-06 | 2018-11-16 | 北京奇艺世纪科技有限公司 | A kind of method for processing video frequency and device |
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