402 results about "Film editing" patented technology

The invention relates to an AI intelligent short video generation method and system based on multi-agent collaboration. The method comprises the following steps: S1, input analysis and sub-shot script generation; s2, obtaining materials; s3, sub-shot video generation; step S4: editing and synthesizing; wherein the plurality of sub-shot video clips are edited and synthesized into a complete video according to a script sequence, and style fusion processing is performed on the whole video by using a picture style unification algorithm; step S5, background music matching; and S6, outputting the slices. Through the structured sub-shot script generation, intelligent material completion, multi-shot style fusion and music synchronization technology, a professional short video of multi-scene coherent narrative can be generated, the structured sub-shot script is automatically generated, and intelligent material completion, picture style unification and music rhythm and emotion expression synchronization are realized.

The invention discloses a video editing method and related equipment, and the method comprises the steps: receiving an editing intention of a user, carrying out the semantic analysis of an intention analysis model, and generating an editing copywriting, a style and a structured instruction; the edited copywriting is split according to the edited copywriting; performing cross-modal analysis on video materials by using a video understanding model trained based on an open-source multi-modal model, and accurately positioning sub-lens segments; secondly, editing the sub-lens segments through an editing model to generate a preliminary sheet, performing quantitative scoring through a video scoring model, and obtaining a scoring result according to a multi-dimensional index; and finally, the result is fed back to the editing model, and iterative adjustment is carried out until a final slice is produced. According to the method, the editing efficiency is improved, the manual operation time is shortened, the material adaptability is enhanced, the personalized requirement is met, the editing effect consistency is improved, the video content understanding is deepened, the editing effect is optimized, the technical threshold is reduced, the existing technical problems are solved comprehensively, and an efficient, intelligent and personalized editing scheme is provided.

The invention discloses a short video intelligent editing method and system based on multi-modal analysis, and relates to the technical field of video editing. The method is used for improving editing efficiency and visual experience and comprises the following steps: extracting lip motion features of a character, visual saliency features of a commodity and a voice emotion intensity value from a target short video stream to form multi-modal time sequence data; afterwards, the voice stream is recorded, a product keyword timestamp is extracted, the alignment degree is calculated through dynamic time warping in combination with a visual saliency peak value, and a preliminary editing point set is generated through weighted evaluation in combination with an emotional intensity value; constructing an editing decision optimization model based on deep reinforcement learning, taking the multi-modal features as state input, adjusting the retention probability of editing points through a joint reward function, and selecting an optimal transition mode; and the lip movement and voice synchronization error before and after the editing point and the emotional and visual continuity of the transition section are analyzed, the discontinuous region is smoothed, and the edited finished product is output, so that precise short video intelligent editing is realized.

The invention relates to an automatic video editing method based on semantic analysis, and belongs to the technical field of video editing. The method comprises the following steps: extracting anchor point information of text content in a streaming media file based on a knowledge graph, establishing a support relationship, and determining a main anchor point, a sub anchor point and a argument anchor point by combining the support relationship and the anchor point information; constructing a dynamic trigger mechanism, setting a verification direction of the dynamic trigger mechanism, determining a semantic extension direction of the anchor point information according to the verification direction, and verifying whether a precondition chain supporting the anchor point information exists or not; and setting a credibility scoring strategy, determining the credibility of the anchor point information according to the logic complexity, the language confidence and the text consistency, forming a sequence set of the anchor point information, and splicing to form a logically coherent video editing text result. According to the method, automatic and intelligent editing of the video is realized based on semantic analysis, and the editing efficiency and quality are remarkably improved.

The invention provides an intelligent self-adaptive video editing method and system based on deep learning, and relates to the technical field of video processing.The method comprises the steps that firstly, a semantic mapping relation between a to-be-edited video material and a preset editing requirement is established, and an editing requirement mapping result is generated, the preset editing demand comprises a content style and a rhythm control demand, and then semantic feature association processing is carried out based on the mapping result to obtain a semantic association feature set comprising lens unit content semantic features and rhythm association features; then calling a pre-trained editing decision model (including a semantic matching module and a rhythm adjusting module) to carry out editing strategy matching on the set, generating a preliminary editing strategy set, generating an initial video editing scheme according to the preliminary editing strategy set, carrying out parameter adjustment on the initial scheme according to a strategy optimization suggestion output by the model, and carrying out video editing on the initial scheme; and a final video editing scheme is obtained, and intelligent self-adaptive editing of the video is realized.

The invention relates to the technical field of editing and special effect generation, in particular to a digital media content intelligent editing and special effect generation system based on artificial intelligence. Comprising a content understanding analysis module, an editing decision module, a special effect generation preview module, an audio processing module, a dynamic transition special effect module, a subtitle generation editing module, a virtual interaction module and a content distribution optimization module. The content understanding analysis module is used for video content identification and sentiment analysis; and the editing decision module is used for recommending an editing point and providing a dynamic editing strategy. The video content can be automatically analyzed, the editing point and the special effect adding position can be identified, the editing and special effect generation efficiency is greatly improved, the editing strategy and the special effect type can be dynamically adjusted according to the video content and the sentiment analysis result, the editing and the special effect can better meet the user requirement and the video content, and the user experience is improved. Abundant editing and special effect options are provided, and the editing and special effect generation process is simplified.

The invention relates to an intelligent video editing method fusing human face features and human voice features, which comprises the steps of input preprocessing, multi-modal analysis, fusion scoring and automatic editing, and adopts a multi-modal mode for analysis, so that the recall rate of key segments is improved, and the efficiency of editing is improved. A personalized editing strategy is supported, facial expression changes and voice emotion peak values are aligned through dynamic time warping, a CLIP-like structure is used for training a bimodal encoder, the human face and the voice are mapped to a unified vector space, the association weight of the human face and the voice is automatically learned, and the intelligent degree of editing is improved.

The invention discloses a video editing method and device, electronic equipment and a nonvolatile storage medium. The method comprises the following steps: acquiring an audio data stream of a target video, and segmenting the audio data stream into a plurality of audio clips; determining a classification result corresponding to the audio clip, and determining a time period corresponding to the audio clip as a candidate ball hitting time period when the classification result is that the audio clip contains the ball hitting sound; acquiring a video frame corresponding to the candidate ball hitting time period in the target video, and judging that the candidate ball hitting time period is a real ball hitting time period under the condition that the visual feature of the video frame is matched with a preset ball hitting rule; and determining an editing time point according to the real ball hitting time period, and editing the target video according to the editing time point to obtain a ball hitting round video clip. The technical problem that the accuracy of ball hitting detection segment detection is low due to the fact that ball hitting detection is conducted only through sound and is easily interfered by environmental noise in the prior art is solved.

The invention relates to the technical field of artificial intelligence content generation, and provides a video generation method and device based on multi-agent cooperation. The method comprises the following steps: selecting a proper copywriting processing agent according to text information input by a user, so as to use the copywriting processing agent to expand or condense a plurality of sub-mirror descriptions; selecting a proper image generation agent; inputting the picture description, the picture style and the mirror operation method in the mirror splitting description into the selected image generation agent to generate a mirror splitting picture; selecting a proper video generation agent; inputting the split picture and the character action and the mirror moving method in the corresponding split description into a selected video generation agent to generate a split video; and selecting a proper automatic editing agent, and performing post-production on the split video to generate a finished video. The technical problems that in the prior art, the video generation process is fragmented, and multi-element collaboration is difficult are solved, and automatic production of complex video content is achieved.

The invention discloses a multi-mode-based short episode video editing method, system and device and a medium, and the method comprises the steps: carrying out the preprocessing of an original short episode video, and obtaining a second short episode video, subtitles and a subtitle timestamp; analyzing the subtitles, and generating a short episode abstract according to an analysis result of the subtitles; according to the short episode abstract and the highlight editing prompt, performing plot analysis and editing on the second short episode video, and performing editing to form a first video set; scoring videos in the first video set according to a multi-dimensional scoring rule, and screening out M highlight video clips before scoring; and adjusting the timestamps of the M highlight video clips according to the subtitle timestamps, and outputting the adjusted M highlight video clips. According to the method and the device, the full link from short video input to short play mixed video output is constructed, a user only needs to input the to-be-edited short play video, the mixed video can be automatically generated, and the video editing efficiency is improved while the video editing threshold is reduced.

The invention discloses a video editing method and device, electronic equipment and a storage medium. The method comprises the following steps: segmenting a to-be-edited video to obtain a plurality of video clips; understanding text generation and subtitle generation are carried out on each video clip, and a clip understanding text and a clip subtitle of each video clip are obtained; determining a target description text based on fragment understanding texts and / or fragment subtitles corresponding to a plurality of target video fragments selected from the plurality of video fragments; and performing video synthesis based on the plurality of target video clips and the target description text to obtain a target video corresponding to the to-be-edited video. According to the method provided by the invention, the video editing efficiency is relatively high, and the video editing cost is relatively low.

The invention discloses a multi-agent collaborative short play digital production system, which belongs to the technical field of artificial intelligence, and comprises a data and state management module driven by a digital thread, which uniformly manages and synchronizes data, states and decisions of all production links through a throughout digital thread; the full-process intelligent production module takes an intelligent control center as a core, decomposes and dispatches a complex task to five professional intelligent agents for cooperative execution, and covers a complete production link from script generation, visual preview, video shooting and special effects to intelligent editing and final sound and picture synthesis; the man-machine collaborative evaluation and feedback closed-loop module provides an interactive interface for human experts to supervise, guide and correct key production nodes and records artificial decisions as feedback to form a closed loop of a continuous optimization system; according to the multi-agent collaborative short play digital production system provided by the invention, the digital thread penetrates through multi-agent collaboration, so that data tracing and state synchronization of the whole process of short play production can be realized, challenges such as narrative continuity, cross-modal consistency and physical authenticity are effectively solved, and the quality of generated content and the production efficiency are remarkably improved.

The invention discloses an intelligent editing style learning and shot arrangement method and device, and the method comprises the steps: firstly carrying out the shot segmentation of an original material video, obtaining a plurality of independent video clips, carrying out the multi-dimensional analysis of each video clip, generating a structured label text containing image semantic features and shooting grammar features, and carrying out the segmentation of the shot; semantic segmentation is carried out on a manuscript to be edited to obtain a plurality of text paragraphs, each text paragraph is matched with at least one edition example, finally prompt words are constructed and input into the generative language model to carry out shot arrangement, and the generative language model outputs a shot arrangement sequence of the current paragraph. The problem of error accumulation caused by the fact that a traditional intelligent editing method depends on an editing script intermediate link is solved, the defect that in the prior art, it is difficult to dynamically learn a specific editing style is overcome, collaborative optimization of semantic matching and editing grammar is achieved, and shot selection accuracy, arrangement fluency and style adaptability are remarkably improved.

The invention provides a video processing method and device, equipment and a storage medium, and the method comprises the steps: segmenting a video material into a plurality of semantically coherent video clips, automatically extracting related video clips from the video material according to the text content provided by a user, and generating corresponding subtitles and voice broadcast ports matched with the related video clips, and finally synthesizing a section of finished video with clear logic and coherent content. According to the scheme, full-process automation from video material generation to final video file generation is realized, a large number of video materials can be quickly processed, the tedious manual editing process in traditional video production is reduced, the dependence on manual intervention is greatly reduced, the operation cost is reduced, the video production process is simplified, the video production efficiency is improved, and the user experience is improved. And the quality and the efficiency of finished products are also improved.

The invention discloses an AI automatic editing method and related equipment, and the method comprises the steps: obtaining a video prototype template selected by a user, prompt information inputted by the user, and original materials uploaded by the user through a user interaction interface, and calling a language large model to generate a structured video script; performing association degree matching on the structured script and the original material through a target detection model, and screening the original material according to a matching result and a quality scoring model to obtain an original video clip; performing background music matching according to the video script to obtain background music, generating voice dubbing and a flower-character chartlet according to the video script, generating video subtitles according to the voice dubbing, performing time axis alignment on each video media element, and synthesizing into a finished video. According to the embodiment of the invention, full-process automatic processing from script generation to video synthesis can be realized, and a high-quality finished video meeting user requirements can be efficiently output. The method can be widely applied to the technical field of automatic editing.

The invention discloses an automatic video editing method and device based on text and shot similarity and a terminal, and belongs to the technical field of artificial intelligence. The method comprises the following steps: determining the end time of a mixed video based on a music interval identification result of specified music; selecting a lens of which the main body label is scenery as a lens head lens; performing similarity analysis with other lenses based on a subject recognition result, a behavior recognition result and a motion calculation result, calculating visual similarity between the lenses based on a deep learning model, recognizing repeated or redundant pictures, and selecting a high-energy lens as an in-chip high-combustion lens; retrieving and intercepting a corresponding lens as a tail lens based on a corresponding segment of the selected end word; and carrying out audio and video mixed cutting and assembling on the specified music, the head lens, the in-chip high-combustion lens and the tail lens. According to the invention, by fusing multi-modal feature analysis and intelligent editing logic generation, efficient and high-quality video automatic production is realized.

Described herein is a computer implemented method for automatically generating a trimmed video clip from a video content item. The method includes: receiving a trim request from a user device, the trim request including the video content item; determining trim parameters for the trimmed video clip, the trim parameters including a trim start time and a trim end time; generating the trimmed video clip based on the trim parameters; and causing display of the trimmed video clip on the user device.

The invention discloses a video editing processing method and system based on artificial intelligence, and the method comprises the steps: obtaining an initial video, extracting the visual semantic features of the initial video through a visual semantic model, and extracting the sound semantic features of the initial video through a sound semantic model; an indication text input by a user is obtained, a preference model of the user is obtained, and the preference model is constructed based on historical behavior data of the user; and processing the visual semantic features and the sound semantic features based on the indication text and the preference model to obtain an edited target video. In this way, the video can be efficiently and accurately edited, and it is ensured that the video editing result can meet the personalized requirements of the user.

The invention discloses an automatic video editing method and system for film list recommendation, and the method comprises the steps: obtaining film data, and carrying out the preprocessing of the film data; according to the preprocessed film data, generating a recommendation list and basic data of a film list by utilizing a preset large model and cue words; generating a copywriting corresponding to the film list data according to the recommendation list and the basic data, and selecting corresponding film resources and background music; and according to the copywriting, the film resource and the background music, performing video synthesis editing, and outputting an automatic edited video recommended by a film list. According to the method, the material combinatorial logic can be dynamically adjusted according to the sheet theme, deep mining and structured application are performed on the sheet recommendation data, and high-efficiency and large-scale sheet recommendation video generation is realized.

The invention provides a video mixing and cutting system, which comprises a material preprocessing unit used for preprocessing an original video material to generate a standardized edited material; the intelligent editing decision-making unit is used for carrying out semantic analysis and editing logic generation on the standardized editing materials so as to generate an editing decision-making instruction; the automatic editing execution unit is used for performing automatic editing processing on the standardized editing material according to the editing decision instruction so as to generate a preliminary mixed cutting video; and the effect optimization output unit is used for performing visual effect enhancement and format optimization on the preliminary mixed cutting video to generate a target mixed cutting video.

The invention introduces an advanced AI-driven anti-piracy system that safeguards audio- video streaming content by generating unique content variations through programmable adjustments to camera cut time codes within a structured list of instructions describing edits of audio-video content. It employs a sophisticated production pipeline to create and distribute these variations ensuring tailored delivery to individual viewer conditions. A recorder meticulously records the distribution of manifest files, enabling the identification of potential sources of piracy. The system includes a detection component that utilizes advanced Artificial Intelligence algorithms to compare the original content with potentially pirated versions, allowing for the effective identification and tracking of unauthorized distributions. This approach represents a significant advancement in combating digital piracy, ensuring content security while maintaining high-quality viewing experiences.

The invention discloses an automatic face score video editing processing method and device based on a face and a terminal, and belongs to the technical field of video processing, and the method comprises the steps: carrying out the shot fragmentation of a video needing to be edited; carrying out frame extraction analysis, and screening out the shot of the target face of which the attribute data of the target face meets the editing requirement; acquiring input specified music as background music, and finding out a position where the music is stuck; splicing all the filtered shot of the target face, splicing the filtered shot of the target face according to the music sticking point position, and editing the spliced video; and taking the edited video as a center, expanding a preset time length towards the outside of the two sides, selecting a segment of lines which accord with the current scene and comprise a target face from the edited video as an end, and generating a final edited video for output. According to the invention, a high-quality short video with a target face can be automatically edited and generated; the problems that a traditional method is serious in audio-visual splitting and insufficient in dynamic adaptability are solved.

The invention relates to the technical field of large models, solves the problems of high cost, low efficiency and the like due to the fact that video editing depends on manual processing in the prior art, and provides an intelligent video editing method, device and equipment based on a graph-to-text large model. The method comprises the following steps: preprocessing an original video to be edited, and obtaining a plurality of frames of first video images after preprocessing; performing clustering analysis on the first video images to obtain a plurality of image sets; inputting each image set into a pre-trained graph-to-text large model to obtain a key tag corresponding to each image set; and comparing each key tag with a preset user instruction, and according to a comparison result, determining a target image set in each image set as an edited target video clip. According to the method, intelligent identification and editing of the video content are realized through a large model, the manual workload is reduced, and reliable technical support is provided for video editing and processing.

The invention relates to an AI-based short video creative material cutting method and device, equipment and a medium. The method comprises the following steps: performing space-time segmentation on an original video material through a pre-training model to generate a video clip set carrying semantic tags and emotion vectors, and performing beat segmentation on an audio material to generate an audio clip set containing semantic tags, emotion vectors and rhythm features; calling knowledge graph analysis based on the target artistic effect type to generate an inconsistency rule set; calculating a conflict value of video and audio clip combinations through a creative tension scoring function, and screening high-score combinations to construct a candidate set; utilizing a sequence optimization algorithm to generate a fragment sequence for maximizing artistic tension and a cutting time point and a transition instruction of the fragment sequence; and synthesis is realized through an editing engine. Therefore, control over artistic audio-visual conflicts is achieved on the premise that basic continuity is guaranteed, the limitation that an existing AI editing system can only be mechanically matched with sounds and pictures is broken through, and the ability of building deep emotion expression is given to a machine for the first time.

The invention provides a short video full-process customer acquisition system based on agent collaboration, and relates to the technical field of artificial intelligence. An input layer of the system is used for receiving task data input by a user; the scheduling layer adopts an agent scheduling engine, and the agent scheduling engine is used for determining at least one subtask and a subtask execution sequence according to the task data, distributing the subtasks based on a publishing and subscribing mode and distributing computing power resources based on a weighted polling algorithm; the function layer comprises an account positioning module, a benchmarking account disassembling module, an account basic building module, a topic selection base building module, a video creation module and an editing and publishing module which are independently packaged in an intelligent agent form; the account number positioning module, the benchmarking account number disassembling module, the account number basic building module, the topic selection base building module, the video creation module and the editing and publishing module execute corresponding subtasks. According to the invention, automatic short video creation guest obtaining can be realized, and the efficiency is improved.

The invention relates to the technical field of multimedia processing, and discloses a video and audio integrated packaging and editing method, device and equipment, and the method comprises the steps: disassembling original video and audio data, respectively extracting audio and video information streams, carrying out semantic analysis through a pre-trained video and audio information analysis model, and generating a semantic sequence of the audio and the video; based on the sequences, key events are identified, an editing positioning shaft is generated, finally, video and audio editing and format packaging are carried out according to the positioning shaft, the requirements of a multi-end platform are met, and corresponding editing files are generated, according to the method, through intelligent analysis and automatic editing, the editing efficiency is greatly improved, manual intervention is reduced, and the editing efficiency is improved. Moreover, the method can accurately adapt to the demands of different platforms, improves the availability and propagation effect of video and audio contents, and solves a problem that the video and audio editing efficiency is low in the prior art.

The invention discloses a video processing method and device based on multi-modal data, equipment and a medium, and relates to the technical field of video processing, and the method comprises the steps: obtaining a multi-modal data analysis result through employing the multi-modal original data of a to-be-processed video; event and narrative processing is carried out according to the multi-modal data analysis result, and an event processing result and a narrative framework are obtained; highlight fragment extraction is carried out based on the multi-modal data analysis result in combination with the event processing result, and a video highlight fragment is obtained; and obtaining a video processing result according to the multi-modal data analysis result, the narrative framework and the video highlight segment. According to the method, data deep multiplexing and full-process automation are realized, the generated video has a clear narrative structure and core bright spot focusing, user resonance can be improved through emotional full-process penetration, meanwhile, the manual intervention cost is greatly reduced, and the generation efficiency is improved compared with that of a traditional editing mode.

The invention provides a live broadcast long video editing method and device based on memory perception collaboration, and relates to the technical field of image processing and video editing. Voice, subtitles and picture actions are analyzed in a linkage mode on a unified time grid, low-complexity characterization of a long video is achieved through an efficient perception module, and the effect of editing the long video is achieved. Cross-fragment core characters, events and semantic clues are precipitated through long-term memory of an entity center, and current perception is fed back through memory retrieval so as to enhance consistency and robustness; on the basis, a three-mode fusion wonderness score is generated, interval optimization and boundary refinement with duration budget constraint are executed, and finally, an editing decision list is output and quickly spliced into a high-quality finely-cut video. According to the invention, the problems of large quantity of long-time live broadcast materials, low efficiency of manual reviewing and editing and easy leakage of wonderful fragments are solved, and the later production efficiency and the quality of the live broadcast content are remarkably improved.

The invention relates to the technical field of artificial intelligence and image processing, can be applied to the field of intelligent medical treatment and finance, and discloses a video editing method and device based on artificial intelligence, equipment and a medium, and the method comprises the steps: obtaining a to-be-edited video, and carrying out the preprocessing of the to-be-edited video; based on a gating mechanism, according to the video content, carrying out dynamic division of spatial-temporal characteristics on the characteristic pattern of the video frame sequence in the video to be edited to obtain a plurality of content-coherent spatial-temporal partitions, and fusing the characteristics of the plurality of spatial-temporal partitions to obtain a fused characteristic; analyzing the fusion features based on a pre-trained segmentation model, determining editing boundary points, and editing the to-be-edited video according to the editing boundary points to generate at least one target video; and generating a final edited video of the to-be-edited video according to the target video. According to the method, feature regions can be dynamically divided according to video contents based on a gating mechanism, space-time joint self-adaptive partitioning is realized, and redundant calculation can be avoided.

The invention relates to the technical field of video editing, solves the problem that how to obtain a video clip is not involved in the prior art, and provides a video editing method, device and equipment based on a multi-modal large model and a medium, and the method comprises the steps: obtaining image description information input by a user and a to-be-edited video; performing semantic segmentation on the to-be-edited video according to the image description information to obtain a plurality of initial segmentation fragments in the to-be-edited video; for each initial boundary frame in each initial segmentation segment, if an adjacent video frame which is adjacent to the initial boundary frame and is not included in the initial segmentation segment exists in the video to be edited, obtaining a target boundary frame according to the adjacent video frame and the initial boundary frame; and determining a target video clip in the video to be edited according to the two target boundary frames in the initial segmentation clip. Dynamic adjustment and optimization of the boundary can be realized, so that the target video clip in the video can be accurately determined.