Automatic fission video generation management platform for limited video materials

Abstract

The invention discloses an automatic fission video generation management platform for limited video materials. The automatic fission video generation management platform comprises a multi-dimensional information replacement engine, a content truncation and recombination module and an automatic scheduling and management system. The multi-dimensional information replacement engine dynamically replaces characters, voices and image elements in the video based on a template structure; the content truncation and recombination module carries out intelligent truncation and sequential recombination on the video clips through semantic recognition and shot segmentation technologies; the automatic scheduling and management system automatically generates multi-version videos based on a rule engine or an AI algorithm, and performs tagging management and distribution. According to the method, the video generation efficiency can be remarkably improved, the manufacturing cost is reduced, diversified and large-scale production of the video content is realized, and the method is suitable for automatic generation and accurate delivery of the video content in multiple scenes such as e-commerce, education and media.

Description

Technical Field

[0001] This invention relates to the field of video content generation and multimedia information processing technology, specifically to an automated fission video generation and management platform for limited video materials. Background Technology

[0002] Currently, short videos are increasingly widely used in e-commerce, education, media, and corporate promotion. However, traditional video production methods rely heavily on manual editing, resulting in low efficiency, high costs, and difficulty in scaling up the production of multiple video versions. Especially when resources are limited, it is difficult to quickly generate diverse video content suitable for different scenarios and audiences, thus limiting the effectiveness and reach of content dissemination. Summary of the Invention

[0003] This invention provides an automated video generation and management platform for limited video materials, which achieves efficient generation and management of video content through intelligent and modular methods.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an automated video generation and management platform for limited video materials, comprising:

[0005] A multi-dimensional information replacement engine is used to dynamically replace text, voice, and image elements in videos based on template structures.

[0006] The content truncation and recombination module is used to intelligently truncate and reassemble video segments in sequence through semantic recognition and shot segmentation technology;

[0007] An automated scheduling and management system is used to automatically generate multiple versions of videos based on rule engines or AI algorithms, and to manage and distribute them with tags.

[0008] Preferably, the multi-dimensional information replacement engine supports multi-modal content replacement, including text-to-speech, image overlay, and dynamic subtitle insertion.

[0009] Preferably, the content truncation and recombination module includes a semantic analysis unit and a shot segmentation unit, which can identify key semantic nodes in the video and perform intelligent segmentation.

[0010] Preferably, the automated scheduling and management system supports intelligent recommendation and generation of video versions based on user behavior data or distribution channel characteristics.

[0011] Preferably, the platform also has a video material library and a template library, supporting batch import of materials and flexible configuration of templates.

[0012] Preferably, the platform provides API interfaces to support integration with third-party content platforms and data analysis systems.

[0013] The beneficial effects of this invention are as follows: it significantly improves video generation efficiency, increasing efficiency by more than 80% compared to manual editing, and can generate hundreds of viral videos in batches per day; it greatly reduces production costs, reduces repetitive manual operations, and lowers costs by 70%; it offers a high degree of diversity in video content, covering more user preference scenarios and improving content conversion rates; and it supports the large-scale generation, management, and tracking of video content, facilitating precise targeting and performance analysis for enterprises across different channels. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the overall structure of the platform of the present invention;

[0016] Figure 2 This is a schematic diagram illustrating the workflow of the content truncation and recombination module of this invention.

[0017] In the diagram: 1. Multidimensional information replacement engine; 2. Content truncation and recombination module; 3. Automated scheduling and management system; 4. Video material library; 5. Template library; 6. Output management interface. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1

[0020] Reference Figure 1 The schematic diagram of the overall structure of the platform of this invention shows an automated video generation and management platform for limited video materials. It mainly includes: a multi-dimensional information replacement engine 1, a content truncation and recombination module 2, and an automated scheduling and management system 3. The platform is also connected to a video material library 4 and a template library 5, and connects to external channels through an output management interface 6.

[0021] The video material library 4 is used to store limited original video materials, such as product demonstration videos, course recordings, and original news clips. The template library 5 stores pre-designed video templates, which define the structure, style, and replaceable elements of the video, such as attributes and rules for subtitle positions, background music, image placeholders, and audio scripts.

[0022] The platform's workflow is as follows:

[0023] Step S101: Preparation of materials and templates.

[0024] Users can batch upload raw video footage to the video footage library 4 through the platform interface. Simultaneously, users can select a suitable template from the template library 5, or create and configure new templates according to business needs. Template configuration includes setting replaceable text variables, image areas, background music options, and voice styles, etc.

[0025] Step S102: Multidimensional information replacement.

[0026] The multi-dimensional information replacement engine 1 loads the selected template and the specified original video footage. Based on template rules, or based on user-input data, the engine dynamically replaces elements in the video.

[0027] Text replacement: For example, replace the title and description text in the template with new marketing copy, and automatically generate dynamic subtitles to be overlaid on the specified position in the video.

[0028] Image replacement: For example, replacing product display images or background images in a video with images of another product.

[0029] Voice replacement: For example, text-to-speech technology can be used to generate new narration in different timbres and languages ​​to replace the original video's audio track or overlay it onto the background music.

[0030] This process generates a batch of preliminary videos that have been personalized on the surface information.

[0031] Step S103: Content truncation and recombination.

[0032] Content truncation and recombination module 2 receives the video after information replacement. This module further restructures the video content to generate versions with different content rhythms and focuses.

[0033] Semantic analysis unit: It performs speech recognition on the audio track of the video and converts it into text, or directly analyzes the subtitle text, and uses natural language processing technology to identify semantic nodes such as key topic sentences, turning points, and summary sentences in the video.

[0034] Shot segmentation unit: Combining computer vision technology, it analyzes changes in video frames and detects shot switching points.

[0035] Intelligent Segmentation and Recombination: The module integrates semantic nodes and shot transition points to intelligently segment the video into multiple meaningful segments, such as "opening remarks," "demonstration of function one," "demonstration of function two," "user reviews," and "summary appeal." Subsequently, according to a preset recombination strategy, the order of these segments is rearranged and combined to form new videos with different narrative logics.

[0036] Step S104: Automated scheduling, management and distribution.

[0037] The automated scheduling and management system 3 is responsible for coordinating the entire process and managing the output.

[0038] Version Generation and Tagging: Based on a preset rule engine or AI algorithm, the system drives the aforementioned modules to generate multiple versions of the final viral videos in batches. Each generated video is automatically tagged, such as "Duration_30s", "Style_Exciting", "Channel_Douyin", "Content Focus_Function Demonstration", etc., and stored in the video library.

[0039] Batch Export and Distribution: Users can filter tags and select videos in batches through the system interface. Output management interface 6 is responsible for batch exporting selected videos to local storage or publishing them directly to designated third-party content platforms via the integrated API.

[0040] Data tracking: The platform can also use APIs to retrieve data such as dissemination volume, click-through rate, and conversion rate from various channels, and associate them with video tags to provide data feedback and optimization basis for subsequent video generation strategies.

[0041] Example 2

[0042] This embodiment is a further refinement of Embodiment 1, focusing on a specific implementation of the content truncation and recombination module 2, referring to... Figure 2 The flowchart shown is as follows:

[0043] S201: Video Input: Receives the video stream processed by the multidimensional information replacement engine 1.

[0044] S202: Semantic Recognition: The semantic analysis unit performs speech recognition on the audio of the video to obtain text information. Subsequently, NLP models, such as BERT and LSTM, are used to extract key sentences, segment topics, and perform sentiment analysis on the text, identifying the start and end timestamps of key semantic segments.

[0045] S203: Shot Segmentation: The shot segmentation unit uses scene detection algorithms, such as histogram difference, edge change rate or deep learning model, to analyze video frame sequence, accurately detect the boundary points of shot switching, and obtain technical shot segments.

[0046] S204: Segment Alignment and Filtering: Aligning and merging semantic segments and shot segments along the timeline. For example, a semantic "function point description" may consist of multiple consecutive shots. The system will filter eligible segments from the merged segment pool according to the reorganization strategy.

[0047] S205: Sequence Reordering: Based on different narrative templates, the selected segments are reordered. The system uses transition effects to smoothly connect adjacent segments, ensuring a smooth viewing experience.

[0048] S206: Output multiple video versions: Finally, output multiple video versions that differ in content and structure for use by the automated scheduling and management system 3.

[0049] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An automated video generation and management platform for limited video materials, characterized in that, include: A multi-dimensional information replacement engine is used to dynamically replace text, voice, and image elements in videos based on template structures. The content truncation and recombination module is used to intelligently truncate and reassemble video segments in sequence through semantic recognition and shot segmentation technology; An automated scheduling and management system is used to automatically generate multiple versions of videos based on rule engines or AI algorithms, and to manage and distribute them with tags.

2. The automated fission video generation and management platform for limited video materials according to claim 1, characterized in that: The multi-dimensional information replacement engine supports multimodal content replacement, including text-to-speech, image overlay, and dynamic subtitle insertion.

3. The automated fission video generation and management platform for limited video materials according to claim 2, characterized in that: The content truncation and recombination module includes a semantic analysis unit and a shot segmentation unit, which can identify key semantic nodes in the video and perform intelligent segmentation.

4. The automated fission video generation and management platform for limited video materials according to claim 3, characterized in that: The automated scheduling and management system supports intelligent recommendation and generation of video versions based on user behavior data or distribution channel characteristics.

5. The automated fission video generation and management platform for limited video materials according to claim 4, characterized in that: The platform also features a video material library and a template library, supporting batch import of materials and flexible configuration of templates.

6. The automated fission video generation and management platform for limited video materials according to claim 5, characterized in that: The platform provides API interfaces to support integration with third-party content platforms and data analysis systems.

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