236 results about "Film editing" patented technology

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 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 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 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 embodiment of the invention provides a non-narrative video editing method and related equipment, and belongs to the technical field of data processing. The method comprises the following steps: acquiring a non-narrative video source material to be edited; performing video understanding processing on the non-narrative video source material to obtain a video content description text and a category label; according to the video content description text and the category label, performing retrieval based on a video editing knowledge base to obtain creative editing logic matched with the non-narrative video source material; and based on creative editing logic, performing analysis and fragment combination on the non-narrative video source material through a multi-modal large model, automatically generating at least one creative edited video, performing score sorting on the generated at least one creative edited video, and outputting a target edited video. According to the embodiment of the invention, the method can achieve the efficient and intelligent video automatic generation which fits the market trend, and also remarkably improves the material creation efficiency and creative quality.

The invention relates to a highlight short video editing method and device, a storage medium and electronic equipment. The method comprises the following steps: segmenting a target video into a plurality of segments taking a shot as a unit, and carrying out multi-modal sentiment analysis on each segment to obtain a multi-modal sentiment vector of each segment; according to the multi-modal emotion vector of each fragment, calculating to obtain an emotion intensity value of each fragment, and according to a time sequence, drawing an emotion arc of the target video by the emotion intensity values of all the fragments; determining an emotion peak value and an emotion turning point from the emotion arc line, and determining a highlight segment corresponding to the emotion peak value and the emotion turning point from all segments; and splicing all the highlight segments according to the time sequence to obtain a highlight short video of the target video. The technical problems that in the prior art, emotion capture is not accurate, a narrative context is missing, and high-quality emotion short video content is difficult to generate rapidly are solved.

A collaborative content generation system uses machine learning to generate a script and content depicting the performance of the script. A director may use the system to generate the script and optionally, may involve one or more collaborators who perform portions of the script. The system may use machine learning to generate or modify a script, a storyboard to visualize the story, a narrator (e.g., the narrator's voice), characters, music, sound effects, etc. A director may assign portions of the script to certain collaborators and select which of their recordings are interleaved into the final collaborative interleaved content series. The collaborators may independently perform their portions and provide clips of their performances to the system, which may then interleave the clips to produce the finalized content.

The invention belongs to the technical field of artificial intelligence and multimedia processing, and discloses an automatic video editing method based on multi-agent collaboration and a related device. The automatic video editing method comprises the following steps: receiving a video editing demand input by a user in a natural language form through a master control agent; performing summary analysis on the media material to be processed, and receiving a structured analysis result returned by the multi-modal analysis agent; carrying out editing planning, generating an ordered execution sequence formed by calling a series of atomization editing tools, calling an atomization editing tool set, and constructing a complete editing project file; and rendering the edited item file through a rendering engine, and outputting a target video file. According to the technical scheme disclosed by the invention, the technical problems existing in the aspects of long video processing, personalized demand response, end-to-end automatic execution capability and the like in the prior art are solved.

The invention relates to the technical field of video editing platforms, in particular to an intelligent semantic understanding and efficient editing algorithm of an intelligent video editing platform, which comprises the following steps: S1, synchronously processing image frames, audio and subtitle texts, extracting time slice semantic content, and combining semantic density, emotion tension and keyword frequency to generate a semantic pulse atlas; s2, based on the semantic pulse atlas, adopting a multi-scale fitting mechanism to identify mutation points, continuous growth segments and peak points, and positioning and sequencing semantic outbreak areas; and S3, in combination with the position and type of the semantic outbreak point and user preference, generating an editing high-energy fragment set, and outputting fragment starting and ending time, type identification and transition suggestions. According to the method, accurate extraction of key video clips and automatic editing instruction generation are realized through an intelligent screening mechanism of multi-modal semantic fusion, abnormal pulse recognition and preference driving, and the editing efficiency and the personalized expression ability are improved.

The disclosed technology uses a media production platform to edit multimedia files with an AI model (e.g., a neural network). The technology can remove retakes, identify highlight clips, and / or generate layouts for multimedia files. The technology can process audio transcripts to exclude retakes by generating a refined transcript and highlighting removed segments. Additionally, the technology can edit audiovisual files by generating scenes based on content and mapping the scenes to relevant layouts, dynamically adjusting based on user input. The technology can generate highlights by applying AI models to create clips and identify topics within the audiovisual file, producing an edited file indicative of the topics. The results, such as the edited files, are presented on the client device.

A device obtains video of an event captured by an image capture device and detects one or more objects within frames of the video. Tracking data for detected objects across frames of the video is also generated for detected objects. Based on the tracking data, the device generates a graph representing detections of objects in different frames and selects an optimal path traversing the graph. The device selects a set of key frames based on nodes along the optimal path and applies one or more reframing methods to the set of key frames to generate a clip comprising a subset of the video. The clip may be distributed to user devices or to a backend server for distribution.

An object of the system according to the embodiment is to efficiently extract an excellent play of a player from a game video and create a highlight reel.SOLUTION: A system according to an embodiment includes a video analysis unit, a performance evaluation unit, a play extraction unit, and a highlight editing unit. The video analysis unit analyzes the game video. The performance evaluation unit evaluates movements and technical performances of the players based on the game video analyzed by the video analysis unit. The play extractor extracts an excellent play evaluated by the performance evaluator. The highlight editing unit edits a highlight reel by connecting the excellent plays extracted by the play extracting unit.SELECTED DRAWING: Figure 1

The invention provides a cloud video processing method and system and a storage medium, and the method comprises the steps: obtaining cloud video data uploaded by a user, determining an editing element and an editing template according to the editing demand of the user, carrying out the editing processing of the cloud video data according to the editing element and the editing template, and obtaining an edited cloud video; acquiring annotation information for the edited cloud video, and annotating the edited cloud video according to the annotation information to obtain an annotated cloud video; obtaining a modified cloud video of the annotation cloud video, and when the modified cloud video meets a video examination requirement, performing video classification on the modified cloud video to obtain a video type; and determining a video pushing plan according to the video type, and performing video pushing on the modified cloud video according to the video pushing plan. According to the embodiment of the invention, the comment information for the edited cloud video is obtained, the edited cloud video can be effectively commented based on the comment information, and the safety of subsequent cloud video pushing is improved.

Embodiments of the present disclosure provide a long memory transformer-based time action positioning method and device. Applied to the field of time action positioning; the method comprises: clipping a target video to obtain a short video set; randomly selecting one or more short videos in the short video set and inputting them into a pre-trained short-term Transformer encoder to obtain the features of the randomly selected one or more short videos; using a long memory module to sample from long-term memory to obtain the features of the short videos in the short video set that have not been selected; inputting the features of the randomly selected one or more short videos and the features of the short videos that have not been selected into a time fusion module to obtain fused video features; and inputting the fused video features into a time boundary positioning module to obtain four-tuples of each action instance. In this way, the speed of time action positioning is improved, the memory consumption of processing resources and the training time are reduced, and faster prediction speed and better action classification accuracy are achieved.

The invention discloses a system and a method for automatically processing a marathon event video based on a multi-mode AI (Artificial Intelligence). The system adopts a micro-service distributed architecture, and comprises a coordination service, an identification service and a synthesis service; the coordination service receives competition information and video data and distributes tasks through a message queue; the identification service performs player number plate identification on the video stream based on a Qwen2.5-VL multi-mode model, and extracts player video clips; and the synthesis service synthesizes the video clip and the match material into a personalized Vlog video, and superposes player score information at the tail of the video clip. The system supports two modes of terminal position triggering and concentrated synthesis after racing, and real-time performance and integrity of video processing are achieved. According to the method, intelligent identification, automatic editing and personalized synthesis of the marathon event video are realized, and the video processing efficiency and the user experience are remarkably improved.

The invention relates to a video editing method and device, electronic equipment and a storage medium. The video editing method comprises the following steps: selecting a video to be edited; processing the to-be-edited video based on a video editing processing model to obtain a plurality of video frames and video frame information corresponding to the to-be-edited video, the video frame information comprising image features and annotation texts of each of the plurality of video frames, and the annotation texts being used for annotating the image features of the video frames; and clustering the plurality of video frames based on the image feature and the annotated text of each video frame to obtain a target video. According to the video editing method and device, the selected video is automatically edited, the video editing efficiency is improved, and the user experience is improved.

The invention discloses a video generation method and a related device, and relates to the field of video processing, and the method comprises the steps: obtaining a first video; wherein the first video is a to-be-edited video, the first video is edited to obtain a second video, the first video has a plurality of plot lines, and the plot lines are main lines or branch lines; generating a description text set based on the first video; wherein the description text set comprises a plurality of plot line description texts, and each plot line description text describes one plot line; selecting one plot line description text from the description text set as a target text; searching a video indicated by the target text from the first video to obtain a second video; wherein the second video comprises the video content of a story line. According to the invention, the probability of plot chaos can be reduced.

The invention relates to a video editing method, a video processing method, terminal equipment, a server and a system. The method comprises the steps of determining at least one to-be-edited video in response to a user intention; sending the at least one video to be edited to a server; a music element issued by the server is received, the music element is associated with the video content to be edited, and the music element comprises card point information; according to the sticking point information, extracting a corresponding target video clip from the at least one to-be-edited video; and generating a video editing result according to the target video clip. Thus, the video editing efficiency and the video editing effect can be improved, the operation burden of the two parties can be balanced through information interaction between the terminal equipment and the server, and the overall video editing process is optimized.

1. The name of the design product: audio and video clip graphical user interface of electronic device. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for audio and video clip, such as: the played video can be clipped. 6. The human-computer interaction mode of the graphical user interface: click the second scissors icon on the left side of the pop-up layer at the bottom of the interface in the front view, the interface jumps to the audio and video clip interface as shown in interface change state diagram 1; drag the slider on the progress bar in the editing area at the bottom of the interface change state diagram 1 interface to crop, click the "complete clip" button on the upper side of the editing area after the cropping is completed, the interface jumps to the interface as shown in interface change state diagram 2, which prompts the successful saving; click the "view details" button on the prompt pop-up layer in the lower right corner of the interface change state diagram 2, the interface jumps to the interface as shown in interface change state diagram 3, which views the clip list interface of the already clipped and successfully saved segments; the chamfered rectangular color block coating area in all the above interfaces represents replaceable content screen, and "XXX" represents replaceable text and / or numbers.

The application discloses a kind of video intelligent slice method based on multi-modal information fusion and semantic constraint, it is related to video content analysis and intelligent editing technical field, it is characterized in that it proposes semantic priority audiovisual collaborative slice scheme, obtains shot interval by shot boundary detection, constructs voice interval and effective word information by voice recognition, adopts voice interval as semantic mask to remove visual cut point in the process of voice expression, and based on fragment length and effective word, content density determination is carried out to long fragment, and further adopts visual re-cutting, audio energy driving and uniform cutting Secondary slicing strategy of division, the method provided by the application solves the problem of semantic fragmentation and content perception loss in the prior art, can obtain video fragment with complete semantics, high content density and appropriate length, and is suitable for various application scenarios such as automatic editing, short video generation and video content retrieval.

The invention discloses an edited content optimization system and method based on a user feedback quantization signal, and belongs to the technical field of video content generation and optimization. The system comprises a user feedback acquisition module, a data modeling and feedback vector generation module, an editing optimization and regeneration module and an automatic comparison and iteration closed loop module. The method comprises the steps of collecting user watching behavior data; modeling the feedback data to generate a feedback vector; inputting the feedback vector into a director language model to adjust video structure parameters; and generating an optimized version and carrying out multiple rounds of test iteration. By establishing an intelligent closed loop of generation-feedback-optimization-regeneration, automatic and continuous optimization of video content based on user feedback is realized, the complete playing rate, click rate and conversion rate of the video are remarkably improved, and the problem that an existing AI editing system lacks learning optimization from user behavior data is effectively solved.

The invention discloses an automatic video editing method and device based on a large model, equipment and a program product, and the method comprises the steps: determining a semantic tag of a multimedia material and semantic correlation between the semantic tag and a required text, and generating material semantic information; constructing a split prompt statement according to the material semantic information and the demand text, and inputting the split prompt statement into a large language model to obtain a split script sequence; determining the material coverage of each split script, determining a missing shot list according to the material coverage, and performing material extension according to the missing shot list to obtain a target material set; generating an initial video frame sequence according to the split script sequence and the target material set, and determining background audio data; and determining a visual feature difference of the adjacent sub-mirrors according to the initial video frame sequence, generating a transition effect according to the visual feature difference, and generating a target synthetic video according to the initial video frame sequence, the transition effect and the background audio data. The video editing efficiency and content quality are improved, and the method can be applied to the technical field of video editing.

The application relates to a kind of adaptive video streaming method and system based on serverless computing, belong to streaming media transmission technical field.System is realized by fine-grained serverless pipeline Video delivery, use stateless function to strengthen the response to video request event, use a kind of near-end strategy optimization PPO of three-end clipping based on deep reinforcement learning algorithm to solve the bit rate adaptive sequence decision problem in video playing process.In addition, dynamic video block quality factor is included in user experience QoE index, to configure QoE model, for each video block is assigned a priority weight, improves the robustness of video bit rate decision, thereby reduces video streaming delay, improves user viewing experience.

This application relates to the field of computer application technology and provides a template matching method and electronic device for editing footage. The method includes: acquiring at least one piece of footage to be edited selected by a user, wherein the footage to be edited includes at least one of video and image; identifying themes of the footage to be edited based on various template themes contained in a template library to obtain multiple templates to be matched from the template library; matching each template to be matched with the footage to be edited according to at least one preset matching index to determine the target matching score corresponding to each template to be matched; and selecting at least one template to be matched as the target template corresponding to the footage to be edited based on the target matching score corresponding to each template to be matched. Therefore, by evaluating the matching degree between templates and footage to be edited from multiple evaluation dimensions, the matching degree between recommended templates and user-selected footage is improved, the final product effect is enhanced, and the user experience is improved.

The invention belongs to the technical field of aerial video editing, and particularly discloses an aerial video AI automatic editing method and system fused with humanity elements, and the method comprises the following steps: receiving aerial materials uploaded by a user, and providing a video template library containing a plurality of scenic spot IPs and humanity elements for the user for selection, wherein each video template is associated with a humanity attribute tag and a technical parameter of a specific scenic spot; based on the video template selected by the user, performing multi-dimensional AI processing on the aerial photography material, including background music matching, subtitle generation, explanation speech synthesis, transition effect addition and aerial photography material embedding; and integrating the processed aerial photography materials according to the sequential logic of the template to generate a complete aerial photography video clip. According to the method, the scenic spot IP and the humanity element are integrated, full-process AI automatic editing of the aerial video can be realized, and the requirements of a user on efficient and high-quality humanity aerial video production are met.

The invention relates to the technical field of video editing, in particular to a pet video collection generation method and device, and solves the problem that in a video collection processing method in the prior art, analysis and editing are not performed from the perspective of pet behaviors, so that a generated collection is lack of attraction and interestingness. The method comprises the following steps: acquiring a plurality of videos including pet images, and decomposing the plurality of videos into multiple frames of original images; determining a target pet according to at least one frame in the multiple frames of original images; obtaining a target image sequence of the target pet according to the multiple frames of original images; according to the target image sequence, determining a plurality of frames of target images related to a preset behavior through a preset behavior recognition method; and generating a video collection of the target pet according to the plurality of frames of target images. The pet behavior can be analyzed, the video collection related to the behavior can be generated, and the interestingness of the collection is improved.

The invention relates to the technical field of image processing, and discloses a video generation method, a readable storage medium, a program product and electronic equipment. The first electronic equipment can execute image-to-video processing on at least part of image materials in the M multimedia materials so as to convert the at least part of image materials into video data, and / or executing video expansion processing on at least part of video materials in the M multimedia materials so as to expand the part of video materials into video data with longer video duration. And then, the first electronic equipment can clip the video data obtained based on the image-to-video processing and / or the video expansion processing and the multimedia materials which are not subjected to the image-to-video processing and the video expansion processing to obtain an editing result. Thus, the at least part of the image materials can be presented in a video mode, and / or the at least part of the video materials can occupy a long time in the editing result, and the visual effect of the editing result can be improved.