Special effect generation method, system and equipment, medium and program product

Abstract

The invention provides a special effect generation method, system and device, a medium and a program product, and the method comprises the steps: judging whether an action indicated in behavior data of a target user is associated with action data of a character in a target video or not, the behavior data of the user comprises at least one of comments or bullet screens sent by the user in the target video; and if an action indicated in the behavior data of the target user is associated with action data of a character in a target video, generating an image special effect based on the behavior data of the target user and action data of a first character, and displaying the image special effect in the target video, the first character is a character associated with the action indicated in the behavior data of the target user. According to the method, the unique personalized special effect can be provided, more users can be attracted, the sense of participation of the users is increased, and therefore the user stickiness is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of real-time video processing technology, and in particular to a special effects generation method, system, device, medium, and program product. Background Art

[0002] Existing video interactive features are relatively limited, primarily limited to basic commentary or barrage. These interactive methods allow users to react to and communicate with content to a certain extent, but the level of personalization is low. During live broadcasts, user interaction with video content is primarily social, such as sending virtual gifts and posting barrage comments. Furthermore, these interactions are often pre-set by the platform, and users can only trigger them with known outcomes, lacking a sense of freshness. For example, in live sports broadcasts, while simple gifting and barrage comments add some interactivity, they lack direct interaction between users and athletes, failing to truly enhance user immersion and engagement. Summary of the Invention

[0003] The embodiments of the present application provide a special effects generation method, system, device, medium and program product to solve the existing problem of how to design more interesting and personalized interactive special effects to improve the user's viewing experience.

[0004] In order to solve the above technical problems, this application is implemented as follows:

[0005] In a first aspect, an embodiment of the present application provides a method comprising:

[0006] Determining whether an action indicated in the target user's behavior data is associated with action data of a character in a target video, wherein the user's behavior data includes at least one of the following: a comment or a barrage sent by the user in the target video;

[0007] If the action indicated in the behavior data of the target user is associated with the action data of a character in the target video, an image special effect is generated based on the behavior data of the target user and the action data of a first character, and the image special effect is displayed in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

[0008] Optionally, generating an image special effect based on the behavior data of the target user and the motion data of the first character includes:

[0009] If the cumulative time that the target user has watched the target video is less than the time threshold, a static picture special effect is generated;

[0010] and / or,

[0011] If the cumulative time that the target user watches the target video is greater than or equal to the time threshold, a dynamic picture effect is generated.

[0012] Optionally, if the image special effect is a static picture special effect;

[0013] Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes:

[0014] determining identity information of the first person based on the motion data of the first person;

[0015] Acquire an identity image of the first person according to the identity information of the first person, wherein the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0016] Determining the identity information of the target user based on the behavior data of the target user;

[0017] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a headshot or the identity image;

[0018] The identity image of the first person is synthesized with the information image of the target user to generate the image special effect.

[0019] Optionally, if the identity information of the first person cannot be confirmed;

[0020] The generating of the image special effects based on the behavior data of the target user and the motion data of the first character further includes:

[0021] determining an action of the first character;

[0022] The input information of the target user is synthesized with the action of the first character to generate the image special effect, wherein the action of the image included in the input information of the target user in the image special effect is consistent with the action of the first character.

[0023] Optionally, if the image special effect is a dynamic picture special effect;

[0024] Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes:

[0025] Based on the motion data of the first person, obtaining the target video within a target time period;

[0026] Determining the identity information of the target user based on the behavior data of the target user;

[0027] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a dynamic image, an avatar, or an identity image, and the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0028] The target video within the target time period is synthesized with the information image of the target user to generate the image special effect.

[0029] Optionally, also include:

[0030] A text special effect is generated based on the behavior data of the target user, and the text special effect is added to the image special effect.

[0031] In a second aspect, an embodiment of the present application provides a special effect generation system, comprising:

[0032] A determination module is configured to determine whether an action indicated in the target user's behavior data is associated with action data of a character in a target video, wherein the user's behavior data includes at least one of the following: a comment or a comment sent by the user in the target video;

[0033] A generation module is used to generate an image special effect based on the behavior data of the target user and the action data of a first character if the action indicated in the behavior data of the target user is associated with the action data of a character in a target video, and display the image special effect in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

[0034] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor, a memory, and a program stored on the memory and executable on the processor, wherein when the program is executed by the processor, the steps of the special effects generation method described in the first aspect above are implemented.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the special effects generation method described in the first aspect above are implemented.

[0036] In a fifth aspect, a computer program product is provided, comprising computer instructions, which, when executed by a processor, implement the steps of the special effects generation method as described in the first aspect above.

[0037] In the present application, it is determined whether the action indicated in the target user's behavioral data is associated with the action data of the character in the target video, and the user's behavioral data includes at least one of the following: comments sent by the user in the target video or barrage sent; if the action indicated in the target user's behavioral data is associated with the action data of the character in the target video, an image special effect is generated based on the target user's behavioral data and the action data of the first character, and the image special effect is displayed in the target video, wherein the first character is the character associated with the action indicated in the target user's behavioral data. The image special effects generated by the present application are based on the determination of the user's own behavioral data and the action data of the character in the target video, and therefore can provide unique personalized special effects, which can attract more users, increase user participation, and thus improve user stickiness. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0039] Figure 1 This is a flow chart of a special effect generation method provided in an embodiment of the present application;

[0040] Figure 2 This is a flowchart of another special effect generation method provided in an embodiment of the present application;

[0041] Figure 3 This is a structural diagram of a special effect generation system provided in an embodiment of the present application;

[0042] Figure 4 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0044] Please refer to Figure 1 , an embodiment of the present application provides a special effect generation method, comprising:

[0045] Step 11: Determine whether the action indicated in the target user's behavior data is associated with the action data of the character in the target video, wherein the user's behavior data includes at least one of the following: a comment or a barrage sent by the user in the target video;

[0046] Optionally, the association in the embodiment of the present application includes at least that the action indicated in the target user's behavior data is consistent with the action of the character in the target video. Taking sports videos as an example, if the barrage sent by the target user includes: "Quick pass the ball!", and the action indicated in the barrage includes "pass the ball", if the athlete in the video makes the "pass the ball" action, then it can be considered that the action indicated in the target user's behavior data is associated with the action data of the character in the target video. Optionally, the association in the embodiment of the present application also includes time association, that is, the target user's behavior data and the action data of the character in the target video occur in a similar time period. If the barrage sent by the user is at time t1, then the time of the action data of the character in the target video should be within the specified time period ta after t1.

[0047] Optionally, the target user is the user who sends barrage or comments. Before determining the association, it is necessary to first obtain the target user's behavioral data. An embodiment of the present application provides an embodiment for collecting the target user's behavioral data: all user comments and barrage data at each moment are collected in units of one second. It is necessary to analyze the network requests of the video platform and find the API interface for barrage or comment data. According to the analysis results, use a suitable programming language (such as Python) and library (such as requests) to simulate HTTP requests to obtain barrage or comment data. Perform necessary parsing and cleaning on the acquired data to extract useful information, such as user ID, nickname, image, comment content, timestamp, etc. Store the processed data in a suitable database or file, where the database can use a relational database (such as MySQL, PostgreSQL).

[0048] Optionally, if you also need to capture the motion data of the person in the target video, you can use the VideoCapture class provided by OpenCV to read frames from the video file and calculate the corresponding frame number based on the time point of the captured image. The video frame rate (FPS) is key information, as it determines the relationship between time and frame number. Use the read() method of the VideoCapture object to read the video frame by frame or directly locate a specific frame. Save each extracted frame and include information such as the frame's timestamp.

[0049] Step 12: If the action indicated in the behavior data of the target user is associated with the action data of a character in the target video, an image special effect is generated based on the behavior data of the target user and the action data of the first character, and the image special effect is displayed in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

[0050] Optionally, use AI technology to analyze the content of the screen, including the scenes, objects, actions, elements, etc. that are associated with the target user's behavioral data. Output the action labels, characters, entities, and keywords of the screen. Obtain the target user's behavior, barrage or comment information. AI technology matches the two and performs multimodal analysis of each frame with the user's barrage or comment information to improve accuracy. Deep learning models, such as convolutional neural networks (CNN) or recurrent neural networks (RNN), can also be trained to identify specific frames and associated text in the frame. If the match is successful, the associated screen and related information such as the target user's behavior data, target user ID, and target image are returned.

[0051] Optionally, the image content of each frame (each moment) may be analyzed, and the content contained in each frame (each moment) may be correlated and matched with the user behavior of each frame (each moment).

[0052] In the present application, it is determined whether the action indicated in the target user's behavior data is associated with the action data of the character in the target video, and the user's behavior data includes at least one of the following: comments sent by the user in the target video or barrage sent; if the action indicated in the target user's behavior data is associated with the action data of the character in the target video, an image special effect is generated based on the target user's behavior data and the action data of the first character, and the image special effect is displayed in the target video, wherein the first character is the character associated with the action indicated in the target user's behavior data. The image special effects generated in the embodiment of the present application are based on the determination of the user's own behavior data and the action data of the character in the target video, and therefore can provide unique personalized special effects, which can attract more users, increase user participation, and thus improve user stickiness.

[0053] In sports videos, more and more users want to interact with players during the event, enhancing their sense of participation and viewing experience. The special effects generation method in the embodiments of this application can also generate special effects based on user behavior data and players' on-site actions or performances. This allows users to interact with players through their own behavior while watching the event, enhancing their interactivity and sense of participation in their favorite events or players.

[0054] Optionally, if the target user's behavior data also indicates a target person, after the action indicated in the target user's behavior data is associated with the action data of the person in the target video, the method further includes: determining whether the first person is associated with the target person.

[0055] Optionally, the association in the embodiment of the present application also includes character association. If the barrage sent by the target user includes: "Number 9, pass the ball", the action indicated in the barrage includes "passing the ball", and the target character (the subject of the action) is player No. 9. If player No. 9 makes the action of "passing the ball", it can be considered that the action indicated in the behavior data of the target user includes the action subject, and is associated with the action data of player No. 9 in the target video.

[0056] For triggering special effects, this can also include enabling special effects that users are unaware of before entering a video. These effects, similar to "easter eggs" in games, automatically trigger when the actions indicated in the target user's behavioral data correlate with the actions of the characters in the target video, thereby increasing the sense of surprise and desire for exploration during viewing. This can break the limitations of existing technologies and achieve a richer and more diverse interactive experience, not only increasing user initiative and participation, but also significantly enhancing the overall viewing experience and increasing user stickiness.

[0057] Of course, this application also includes another possible embodiment:

[0058] Optionally, the target user can be used as the subject of the collection. If the user needs to use the special effect generation method in the embodiment of the present application, the user is used as the target user, and the comments and barrage data sent by the target user are collected. Before entering the target video or while watching the target video, the user can choose whether to turn on the special effect (generate image special effects);

[0059] If you choose to turn on special effects, the node where the user performs the action will be used as the node to start the matching program. That is, if the user makes a comment or barrage at time t1, the action data indicated in the user's behavior data will be analyzed and matched with the screen content in the video t1-t2. If the match is successful, the special effects will be triggered.

[0060] Through the embodiments of the present application, users can actively set whether to match and generate special effects, respect user choices, and generate special effects based on user needs. If the user wants to generate special effects, the video direction will be actively predicted during the video or live broadcast, which will stimulate the user to generate more behavioral data (such as sending more barrages and comments), enhance the interactivity between the user and the target video, and the user will feel more involved in the prediction process, which can enhance the enthusiasm for participating in the interaction.

[0061] Optionally, the display of image effects can execute the display logic of the barrage. For example, the image effects can be displayed in a corner of the current screen, in the center of the screen, scrolling or overlaying, etc. The specific display scheme can be set uniformly by the system or customized by the user.

[0062] Optionally, users can also choose to save the image effects locally or upload them to the cloud.

[0063] If the association is successful, the special effect triggering conditions are met, and the user's viewing time of the target event can also be obtained based on the user ID:

[0064] The method according to claim 1, wherein generating the image special effects based on the behavior data of the target user and the motion data of the first character comprises:

[0065] If the cumulative time that the target user has watched the target video is less than the time threshold, a static picture special effect is generated;

[0066] and / or,

[0067] If the cumulative time that the target user watches the target video is greater than or equal to the time threshold, a dynamic picture effect is generated.

[0068] Optionally, users with different viewing times can generate different special effects and have different display times to generate differentiated special effects. Please refer to Figure 2 For example, if the user's viewing time is less than 30 minutes, a static image is triggered and displayed on the current video screen for 10 seconds. If it is more than 30 minutes, a dynamic image special effect is triggered and displayed on the current video screen for 20 seconds. In the embodiment of the present application, as the viewing time increases, the special effects display will become richer and more diverse. For the same user, the short static image special effects in the early stage encourage the user to continue watching, while the dynamic image special effects in the later stage can further enhance the pleasure of the viewing process. For different users, different special effects are triggered for users with different viewing time, providing a customized interactive experience and increasing user stickiness and satisfaction.

[0069] In addition to determining the special effects content based on viewing time, you can also directly set the special effects type, such as static image effects and dynamic image effects.

[0070] Optionally, if the image special effect is a static picture special effect;

[0071] Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes:

[0072] determining identity information of the first person based on the motion data of the first person;

[0073] Acquire an identity image of the first person according to the identity information of the first person, wherein the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0074] Determining the identity information of the target user based on the behavior data of the target user;

[0075] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a headshot or the identity image;

[0076] The identity image of the first person is synthesized with the information image of the target user to generate the image special effect.

[0077] Optionally, if the generated image effect is a static image effect, the identity information of the first person can be determined from the action data associated with the action data within the specified time when the target user generates the action data, and the identity image of the first person and the information image of the target user can be obtained. The image information can be obtained through tracking technology. Taking sports videos as an example, a 3D athlete tracking (3DAT) system can be used to capture the athlete's movements and postures in real time, and an AI algorithm can be used to analyze which task the first person is in. The first person's biometric information, such as the iris, can also be used. Taking sports videos as an example, the athlete's number plate can also be used to obtain the athlete.

[0078] Optionally, when the identity information of the first person is determined based on the scene, the video source interface can be called to obtain the identity information of the first person, obtain the identity image of the first person, and obtain the information image of the target user based on the identity information of the target user. Based on the behavior data of the target user, the identity information of the target user (such as user ID, etc.) is determined. When obtaining the user information image, at least the avatar or the identity image is included. The user's information image can be uploaded by the user in advance, or the user can be requested to input when generating special effects. If the user does not want to input, the user's avatar can be used directly.

[0079] Optionally, the image generation function in the embodiment of the present application integrates the AI automatic cutout technology of the Canva tool to take out the main characters of the two pictures, and integrates Photoshop, GIMP and other software to edit and synthesize the pictures, and uses AI to render them into more natural collaborative expressions or actions. At this time, the background is abstracted according to the expression or the background image of the picture at this moment (if it is a sports event, it is the background image of the current stadium). Use the rendering background function in the module to render the background onto the picture at this time, and combine the user's barrage or comment data with the module function to generate text and display it on the picture. The picture is corrected and rendered by AI technology to make it more realistic and displayed on the interface. Optionally, if the user does not want to input, the user's avatar can be used, and the character in the avatar can be extracted. If the character does not exist in the avatar, the avatar is directly synthesized with the identity image of the first character.

[0080] Optionally, if the identity information of the first person cannot be confirmed;

[0081] The generating of the image special effects based on the behavior data of the target user and the motion data of the first character further includes:

[0082] determining an action of the first character;

[0083] The input information of the target user is synthesized with the action of the first character to generate the image special effect, wherein the action of the image included in the input information of the target user in the image special effect is consistent with the action of the first character.

[0084] Optionally, if the scene cannot determine the identity of the first person, the action of the first person at this time can be identified and combined with the user image to generate a special effect, so that the target user's information image is synthesized with the action of the first person. At this time, the rendered image is the image of the user performing the action of the first person in the corresponding screen. The synthesis technology is consistent with the above and is displayed on the current screen. Taking sports events as an example, if the "pass" sent by the user's barrage is associated with a certain player, but the player's identity information is not successfully identified, the person contained in the target user's information image is synthesized with the "pass" action. If the target user's information image does not contain a person, a special effect similar to the information image passing the ball is generated in the picture, which is more interesting.

[0085] Optionally, if the image special effect is a dynamic picture special effect;

[0086] Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes:

[0087] Based on the motion data of the first person, obtaining the target video within a target time period;

[0088] Determining the identity information of the target user based on the behavior data of the target user;

[0089] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a dynamic image, an avatar, or an identity image, and the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0090] The target video within the target time period is synthesized with the information image of the target user to generate the image special effect.

[0091] Optionally, if the image effect is a dynamic image effect, and if the association is successful and the trigger conditions match the generated image, a dynamic image is generated. Adobe Premiere Pro is used to retrieve the target video within the target time period from the cached video source, for example, the first three seconds of the action data. For static images, any necessary editing can be performed, such as resizing, cropping, and color correction, to ensure compatibility with the video. The module's animation function can be used to add dynamic effects to static images, making them more vivid in the video. This can also be achieved by adding transitions, animations, or masks. If the user has uploaded a dynamic image, this step can be omitted and the image can be directly synthesized with the athlete's dynamic image. Both videos are first pre-processed, including background and white noise extraction, and key feature extraction. The module's functions are then called to combine the two videos into a single video and design the dynamic effects, which involves the AI model library. The synthesis process may involve overlaying, replacement, and blending. Furthermore, to ensure the color style of the image and video is consistent, color correction technology is required. This can be achieved by adjusting parameters such as brightness, contrast, and color balance. During the dynamic effects generation process, you can add audio to synchronize user comments or comments with the generated audio and text. After editing, select the appropriate format and quality settings as needed to export the final video file. Call the module's function interface to display the video on the current page. These dynamic image effects can produce more vivid results, enhancing the fun and user experience.

[0092] Optionally, also include:

[0093] A text special effect is generated based on the behavior data of the target user, and the text special effect is added to the image special effect.

[0094] Optionally, if the image effect is a static one, the user's comments or comments can be combined to generate text and displayed on the image. If the image effect is a dynamic one, the user's comments or comments can be added to each frame using the module interface to make the entire image more coordinated. By adding text effects, the correlation between user behavior data and the current image effect can be further increased, enhancing the user's interactive experience.

[0095] Optionally, in the embodiments of the present application, a special effects synthesis module can be used to synthesize the associated first person's identity image or action with the target user's information image into a static image or animated image. The synthesis technology makes the image or animated image more realistic. Different backgrounds can be added according to the corresponding different scenes, and special effects such as text can be added according to user comments or comments.

[0096] Please refer to Figure 2 , this embodiment of the application further provides a special effect generation system 20, including:

[0097] A determination module 21 is configured to determine whether an action indicated in the target user's behavior data is associated with action data of a character in a target video, wherein the user's behavior data includes at least one of the following: a user sending a comment or a barrage in the target video;

[0098] The generation module 22 is used to generate an image special effect based on the behavior data of the target user and the action data of the first character if the action indicated in the behavior data of the target user is associated with the action data of the character in the target video, and display the image special effect in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

[0099] In the embodiment of the present application, optionally, the generating module 22 includes:

[0100] A static module is used to generate a static picture effect if the cumulative time the target user has watched the target video is less than a time threshold;

[0101] and / or,

[0102] The dynamic module is used to generate dynamic picture effects if the cumulative time for the target user to watch the target video is greater than or equal to a time threshold.

[0103] Optionally, if the image special effect is a static picture special effect;

[0104] The generating module 22 includes:

[0105] a first synthesis module, configured to determine identity information of the first person based on the motion data of the first person;

[0106] Acquire an identity image of the first person according to the identity information of the first person, wherein the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0107] Determining the identity information of the target user based on the behavior data of the target user;

[0108] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a headshot or the identity image;

[0109] The identity image of the first person is synthesized with the information image of the target user to generate the image special effect.

[0110] Optionally, if the identity information of the first person cannot be confirmed;

[0111] The generating module 22 includes:

[0112] a second synthesis module, determining the action of the first character;

[0113] The input information of the target user is synthesized with the action of the first character to generate the image special effect, wherein the action of the image included in the input information of the target user in the image special effect is consistent with the action of the first character.

[0114] Optionally, if the image special effect is a dynamic picture special effect;

[0115] The generating module 22 includes:

[0116] A third synthesis module, based on the motion data of the first person, obtains the target video within a target time period;

[0117] Determining the identity information of the target user based on the behavior data of the target user;

[0118] Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a dynamic image, an avatar, or an identity image, and the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image;

[0119] The target video within the target time period is synthesized with the information image of the target user to generate the image special effect.

[0120] Optionally, the special effect generation system 20 further includes:

[0121] The text module is used to generate text effects based on the behavior data of the target user, and add the text effects to the image effects.

[0122] The special effects generation system provided in the embodiment of the present application can achieve Figure 1 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0123] The present application embodiment provides an electronic device 30, see Figure 4 As shown, Figure 3 This is a principle block diagram of an electronic device 30 according to an embodiment of the present application, which includes a processor 31, a memory 32, and a program or instruction stored in the memory 32 and executable on the processor 31. When the program or instruction is executed by the processor, the steps in any one of the special effects generation methods of the present application are implemented.

[0124] An embodiment of the present application provides a readable storage medium, which stores programs or instructions. When the programs or instructions are executed by a processor, the various processes of the embodiments of the special effects generation method such as any one of the above-mentioned ones are implemented, and the same technical effects can be achieved. To avoid repetition, they will not be repeated here.

[0125] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0126] The present application also provides a computer program product including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of any of the special effects generation method embodiments shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0127] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0128] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, and storage of user personal information involved in the technical solutions disclosed herein comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken with respect to user personal information to prevent unauthorized access to user personal information data and maintain the security of user personal information and network security.

[0129] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0130] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a service classification device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0131] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A special effect generation method, characterized in that: include: Determining whether an action indicated in the target user's behavior data is associated with action data of a character in a target video, wherein the user's behavior data includes at least one of the following: a comment or a barrage sent by the user in the target video; If the action indicated in the behavior data of the target user is associated with the action data of a character in the target video, an image special effect is generated based on the behavior data of the target user and the action data of a first character, and the image special effect is displayed in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

2. The method according to claim 1, characterized in that Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes: If the cumulative time that the target user has watched the target video is less than the time threshold, a static picture special effect is generated; and / or, If the cumulative time that the target user watches the target video is greater than or equal to the time threshold, a dynamic picture effect is generated.

3. The method according to claim 1, characterized in that If the image special effect is a static picture special effect; Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes: determining identity information of the first person based on the motion data of the first person; Acquire an identity image of the first person according to the identity information of the first person, wherein the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image; Determining the identity information of the target user based on the behavior data of the target user; Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a headshot or the identity image; The identity image of the first person is synthesized with the information image of the target user to generate the image special effect.

4. The method according to claim 3, characterized in that If the identity of the first person cannot be confirmed; The generating of the image special effects based on the behavior data of the target user and the motion data of the first character further includes: determining an action of the first character; The input information of the target user is synthesized with the action of the first character to generate the image special effect, wherein the action of the image included in the input information of the target user in the image special effect is consistent with the action of the first character.

5. The method according to claim 1, wherein If the image special effect is a dynamic picture special effect; Generating the image special effects based on the behavior data of the target user and the motion data of the first character includes: Based on the motion data of the first person, obtaining the target video within a target time period; Determining the identity information of the target user based on the behavior data of the target user; Acquire an information image of the target user according to the identity information of the target user, wherein the information image includes at least one of the following: a dynamic image, an avatar, or an identity image, and the identity image includes at least one of the following: a portrait photo, a digital human image, or a cartoon image; The target video within the target time period is synthesized with the information image of the target user to generate the image special effect.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: A text special effect is generated based on the behavior data of the target user, and the text special effect is added to the image special effect.

7. A special effect generation system, characterized in that: include: A determination module is configured to determine whether an action indicated in the target user's behavior data is associated with action data of a character in a target video, wherein the user's behavior data includes at least one of the following: a comment or a comment sent by the user in the target video; A generation module is used to generate an image special effect based on the behavior data of the target user and the action data of a first character if the action indicated in the behavior data of the target user is associated with the action data of a character in a target video, and display the image special effect in the target video, wherein the first character is the character associated with the action indicated in the behavior data of the target user.

8. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the steps of the special effect generation method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that A computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the special effect generation method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the special effect generation method according to any one of claims 1 to 6.

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