WO2020186934A1 - Procédé, appareil et dispositif électronique pour générer un arrière-plan dynamique contenant une animation - Google Patents

Procédé, appareil et dispositif électronique pour générer un arrière-plan dynamique contenant une animation Download PDF

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Publication number
WO2020186934A1
WO2020186934A1 PCT/CN2020/074369 CN2020074369W WO2020186934A1 WO 2020186934 A1 WO2020186934 A1 WO 2020186934A1 CN 2020074369 W CN2020074369 W CN 2020074369W WO 2020186934 A1 WO2020186934 A1 WO 2020186934A1
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Prior art keywords
animation
specific area
target object
input information
area
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PCT/CN2020/074369
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English (en)
Chinese (zh)
Inventor
郭冠军
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北京字节跳动网络技术有限公司
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Publication of WO2020186934A1 publication Critical patent/WO2020186934A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T13/00—Animation
    • G06T13/20—3D [Three Dimensional] animation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/21—Server components or server architectures
    • H04N21/218—Source of audio or video content, e.g. local disk arrays
    • H04N21/2187—Live feed
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
    • H04N21/4312—Generation of visual interfaces for content selection or interaction; Content or additional data rendering involving specific graphical features, e.g. screen layout, special fonts or colors, blinking icons, highlights or animations

Definitions

  • the present disclosure relates to the field of data processing technology, and in particular, to an animation generating method, device and electronic device including a dynamic background.
  • a virtual anchor is provided to anthropomorphically broadcast the live content and provide necessary guidance for the live broadcast. Thereby enhancing the presence and interactivity of the live broadcast and improving the effect of the web live broadcast.
  • Expression simulation for example, mouth movement simulation
  • the current realization of expression simulation is mainly based on text-driven, natural voice-driven and audio-video hybrid modeling methods to drive the facial expressions of characters.
  • the text-driven approach is usually the TTS (Text to Speech, text-to-speech) engine that converts the input text information into the corresponding phoneme sequence, phoneme duration, and corresponding voice waveform, and then select the corresponding model unit in the model library , Through smooth processing and corresponding synchronization algorithm, finally present the voice and facial expression actions corresponding to the input text content.
  • TTS Text to Speech, text-to-speech
  • the emoji simulation in the prior art has a single or even distorted emoji simulation, which is more like a "robot" performing a performance, and the fidelity of the emoji action is still far from the expression of a real person.
  • the embodiments of the present disclosure provide a method, device and electronic device for generating an animation including a dynamic background, which at least partially solves the problems existing in the prior art.
  • an embodiment of the present disclosure provides a method for generating an animation including a dynamic background, including: obtaining a reconstruction model related to a specific area, a first element, and a second element of a target object, the specific area belonging to the A part of the target object, the first element and the second element are located in the specific area;
  • While generating the first animation dynamically selecting an animation matching the first animation from a plurality of preset animations as the background animation of the first animation;
  • a final animation related to the input information is generated.
  • the method before obtaining the reconstruction model related to the specific area, the first element and the second element of the target object, the method further includes:
  • a plurality of images including the target object are acquired, and based on the plurality of images, a reconstruction model related to the specific area, the first element and the second element of the target object is trained.
  • the training of the reconstruction model related to the specific area, the first element and the second element of the target object includes:
  • the texture map of the specific area is determined.
  • the training of the reconstruction model related to the specific area, the first element and the second element of the target object includes:
  • the detected feature points into a first type feature point and a second type feature point, the first type feature point is used to form a first closed area, and the second type feature point is used to form a second closed area;
  • a first color is filled in the first closed area, and a second color is filled in the second closed area, and the first color is different from the second color.
  • the training of the reconstruction model related to the specific area, the first element and the second element of the target object includes:
  • a third color is filled in the third closed area.
  • the determining the texture feature of the specific area related to the input information, the action of the first element, and the action of the second element based on the reconstruction model includes :
  • the motion parameters obtained after parsing the input information are matched to the first element and the second element to form an action of the first element and the second element.
  • the dynamically selecting an animation matching the first animation from a plurality of preset animations as the background animation of the first animation includes:
  • Analyze the current scene of the input information dynamically select an animation that matches the current scene from a plurality of preset animations as the background animation.
  • the generating a final animation related to the input information based on the first animation and the background animation includes:
  • the specific area is a face area
  • the first element is an eye
  • the second element is a mouth
  • an animation generating device including a dynamic background, including:
  • the acquiring module is used to acquire a reconstruction model related to a specific area, a first element and a second element of a target object, the specific area belongs to a part of the target object, and the first element and the second element are located in the Within a specific area
  • the determining module is configured to determine, based on the reconstruction model, the texture feature of the specific area related to the input information, the action of the first element and the action of the second element, the texture feature of the specific area, the The actions of the first element and the actions of the second element form a first animation related to the input information;
  • the selection module is configured to dynamically select an animation matching the first animation from a plurality of preset animations as the background animation of the first animation while generating the first animation;
  • a generating module is used to generate a final animation related to the input information based on the first animation and the background animation.
  • an embodiment of the present disclosure also provides an electronic device, which includes:
  • At least one processor and,
  • a memory communicatively connected with the at least one processor; wherein,
  • the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute any of the foregoing first aspect or any implementation of the first aspect Including dynamic background animation generation method.
  • embodiments of the present disclosure also provide a non-transitory computer-readable storage medium that stores computer instructions that are used to make the computer execute the first aspect or the first aspect described above.
  • An animation generating method including a dynamic background in any implementation manner of one aspect.
  • the embodiments of the present disclosure also provide a computer program product.
  • the computer program product includes a computing program stored on a non-transitory computer-readable storage medium.
  • the computer program includes program instructions. When executing, the computer is caused to execute the animation generating method including the dynamic background in the foregoing first aspect or any implementation manner of the first aspect.
  • the animation generation solution including dynamic background in the embodiment of the present disclosure includes obtaining a reconstruction model related to a specific area, a first element, and a second element of a target object.
  • the specific area belongs to a part of the target object.
  • the first element and the second element are located in the specific area; based on the reconstruction model, the texture feature of the specific area related to the input information, the action of the first element and the action of the second element are determined, so The texture feature of the specific area, the action of the first element, and the action of the second element form a first animation related to the input information; while the first animation is generated, the preset Among the animations, an animation matching the first animation is dynamically selected as a background animation of the first animation; based on the first animation and the background animation, a final animation related to the input information is generated.
  • FIG. 1 is a schematic diagram of an animation generation process including a dynamic background provided by an embodiment of the disclosure
  • FIG. 2 is a schematic diagram of another animation generation process including a dynamic background provided by an embodiment of the present disclosure
  • FIG. 3 is a schematic diagram of another animation generation process including a dynamic background provided by an embodiment of the present disclosure
  • FIG. 4 is a schematic diagram of another animation generation process including a dynamic background provided by an embodiment of the present disclosure
  • FIG. 5 is a schematic structural diagram of an animation generating device including a dynamic background provided by an embodiment of the disclosure
  • FIG. 6 is a schematic diagram of an electronic device provided by an embodiment of the disclosure.
  • the embodiment of the present disclosure provides a method for generating an animation including a dynamic background.
  • the method for generating an animation containing a dynamic background provided in this embodiment can be executed by a computing device, which can be implemented as software, or as a combination of software and hardware, and the computing device can be integrated in a server, terminal device, etc. .
  • an animation generating method including a dynamic background includes the following steps S101-S104:
  • the target object can be a real person who can broadcast on the Internet, or other objects with information dissemination functions, such as TV programs. Hosts, news program announcers, teachers who give lectures, etc.
  • the target object is usually a person with a communication function. Since this type of person usually has a certain reputation, when there is a large amount of content that the target object needs to broadcast including voice and/or video actions, it usually costs more. At the same time, for live broadcast programs, the target object usually cannot appear in multiple live broadcast rooms (or multiple live channels) at the same time. At this time, if you want to present an effect such as "Anchor Clone", it is usually difficult to achieve this effect through live broadcast by real people.
  • the reconstruction model which can predict the image and actions of the target object based on the input information, thereby generating actions and expressions that match the input information. For example, for a piece of news that needs to be broadcast, the target audience can broadcast the news in the form of a news broadcaster.
  • the solution of the present disclosure only selects the component elements that are most relevant to the identification of the target object: the specific area, the first element and the second element.
  • the specific area is the face area of the target object
  • the first element is the eyes of the target object
  • the second element is the mouth of the target object.
  • the various actions and expressions of the target object in the video can be predicted through video animation.
  • the fidelity image can be used to generate a video file containing the actions and expressions of the target object.
  • the fidelity image can be used as all frames or key frames of the video file, and the fidelity image contains information that matches the input information.
  • the input information can be in multiple ways.
  • the input information can be that the target object needs to play a piece of text or a piece of audio content at the same time during the animation display process, that is, the input information can be in the form of text or audio.
  • the target object can produce different animations.
  • the input information is transformed into parameters matching the texture map and the shape constraint map, and the reconstruction model obtained after training is used to finally complete the guarantee by calling the texture map and the shape constraint map Image generation.
  • the texture map of the specific area of the target object and the shape constraints of the first element and the second element can be given, and the trained reconstruction model can be used to predict the image of the two-dimensional anchor image.
  • the continuous first element The shape constraint of the second element and the fixed texture of the specific area are used as input to predict the continuous animation image of the target object.
  • the background animation can be a variety of different types of background animation, for example, it can be serious, lively, happy, sad, and other different styles of animation.
  • the background animation has a certain length so that it can be called easily.
  • the background animation When calling the background animation, it is necessary to analyze the current scene of the input information. Based on the results of the analysis, dynamically select the animation that matches the current scene from the preset multiple animations as the background animation. For example, if the analysis knows that the current input information is excited, then the excited background animation is called. When a change in the scene of the input information is detected, even if the currently called background animation has not been played, it will switch to call the background animation matching the changed scene. After the currently called background animation is played, if it is found that the current scene of the input information has not changed, the current background animation will continue to be played in a loop.
  • S104 Generate a final animation related to the input information based on the first animation and the background animation.
  • the final animation related to the input information is generated.
  • the final animation can be stored or disseminated in the form of video files.
  • the background animation is switched. For this, it can be determined whether the background animation is composed of multiple different types of animation splicing, and if so, smooth processing is performed on the different types of animation. Make the transition between different types of animation as background animation more natural.
  • the reconstruction model is obtained through neural network training. For this reason, before obtaining the reconstruction model related to the specific area, the first element and the second element of the target object, it is also necessary to collect multiple images containing the target object. Images, training a reconstruction model related to the specific area, the first element and the second element of the target object.
  • training a reconstruction model related to a specific region, first element, and second element of the target object can be performed through a specific implementation manner according to an embodiment of the present disclosure, which can include:
  • S201 Detect specific areas on the multiple images to obtain a target area.
  • the target area may be a face area.
  • face areas existing on multiple images can be detected by means of face detection.
  • S202 Perform 3D reconstruction on the target area to obtain a 3D area object.
  • the constituent objects on the target object can be selected to model the target object.
  • Various methods can be used for 3D modeling of the target area. For example, a depth value can be added on the basis of the two-dimensional pixel values of the multiple image planes, and the depth value can be obtained based on the brightness values of the multiple images.
  • S203 Acquire a three-dimensional grid of the 3D area object, where the three-dimensional grid includes preset coordinate values.
  • the 3D area object uses a three-dimensional grid to describe its specific location.
  • specific coordinate values are set for the three-dimensional grid.
  • the three-dimensional grid can be described by setting two-dimensional plane coordinates and spatial height coordinates.
  • S204 Determine a texture map of the specific region based on pixel values on different three-dimensional grid coordinates.
  • the pixel values on different three-dimensional grid coordinates can be connected together to form a grid plane, which forms a texture map of a specific area.
  • the training is related to the specific area of the target object, the first element and Refactored models related to the second element, including:
  • S301 Perform feature point detection on the first element on the multiple images.
  • the contour and pupil of the eye can be used as feature objects, and feature points related to the contour and pupil of the eye can be obtained through feature detection.
  • the first element is composed of at least two components (for example, pupil and sclera). Based on the different parts to which the feature points belong, the detected feature points are divided into first type feature points and second type feature points, for example, the first Type feature points are feature points related to the pupil, and the second type feature points are feature points related to the sclera.
  • the first type feature points and the second type feature points are feature points related to the pupil
  • the second type feature points are feature points related to the sclera.
  • S303 Fill a first color in the first closed area, and a second color in the second closed area, where the first color is different from the second color.
  • the training of a reconstruction model related to a specific area, a first element, and a second element of the target object includes:
  • S401 Perform feature point detection on the second element on the multiple images.
  • the feature setting of the second element can detect the feature points related to the second element.
  • the entire mouth can be used as a feature object, and the feature points related to the mouth can be obtained through feature detection.
  • S402 Form a third closed area based on all the detected feature points.
  • a closed area can be formed by connecting all the feature points together, and then a third closed area can be obtained.
  • the third closed area can be filled with a color matching the second element. Taking the mouth as an example, the third closed area can be filled with red that matches the mouth.
  • the contour of the specific area of the target object is predicted, and the texture map determined by the reconstruction model is filled in the predicted contour, thereby obtaining the contour of the specific area of the target object Figure (e.g., face contour map).
  • the motion parameters obtained after parsing the input information are matched to the first element and the second element, and the actions of the first element and the second element are formed.
  • the input information may be in multiple ways, for example, the input information may be in the form of text or audio.
  • the input information is transformed into a first analysis result after data analysis.
  • the first analysis result includes parameters matching the texture map and the shape constraint map of the first element and the second element.
  • the reconstruction model obtained after training is used to pass The texture map and the shape constraint map are called to finally complete the generation of the target object prediction action.
  • the first analysis result contains the motion amplitude parameters for the first element and the second element on the target object. Take the mouth as an example. When the mouth is fully opened, the motion amplitude can be quantified as 1. When the mouth is fully closed, the motion amplitude It can be quantified as 0. By quantifying the value between 0 and 1, the intermediate state of the mouth between fully opened and fully closed can be described.
  • an animation generating device 50 containing a dynamic background including:
  • the obtaining module 501 is configured to obtain a reconstruction model related to a specific area, a first element, and a second element of a target object, the specific area belongs to a part of the target object, and the first element and the second element are located in the target object. Said within a specific area.
  • the target object can be a real person who can broadcast on the Internet, or other objects with information dissemination functions, such as TV programs. Hosts, news program announcers, teachers who give lectures, etc.
  • the target object is usually a person with a communication function. Since this type of person usually has a certain reputation, when there is a large amount of content that the target object needs to broadcast including voice and/or video actions, it usually costs more. At the same time, for live broadcast programs, the target object usually cannot appear in multiple live broadcast rooms (or multiple live channels) at the same time. At this time, if you want to present an effect such as "Anchor Clone", it is usually difficult to achieve this effect through live broadcast by real people.
  • the reconstruction model which can predict the image and actions of the target object based on the input information, thereby generating actions and expressions that match the input information. For example, for a piece of news that needs to be broadcast, the target audience can broadcast the news in the form of a news broadcaster.
  • the solution of the present disclosure only selects the component elements that are most relevant to the identification of the target object: the specific area, the first element and the second element.
  • the specific area is the face area of the target object
  • the first element is the eyes of the target object
  • the second element is the mouth of the target object.
  • the determining module 502 is configured to determine, based on the reconstruction model, the texture feature of the specific area, the action of the first element and the action of the second element related to the input information, the texture feature of the specific area, the The action of the first element and the action of the second element form a first animation related to the input information.
  • the various actions and expressions of the target object in the video can be predicted through video animation.
  • the fidelity image can be used to generate a video file containing the actions and expressions of the target object.
  • the fidelity image can be used as all frames or key frames of the video file, and the fidelity image contains information that matches the input information.
  • the input information can be in a variety of ways.
  • the input information can be in the form of text or audio.
  • the input information is transformed into parameters matching the texture map and the shape constraint map, and the reconstruction model obtained after training is used to finally complete the guarantee by calling the texture map and the shape constraint map Image generation.
  • the texture map of the specific area of the target object and the shape constraints of the first element and the second element can be given, and the trained reconstruction model can be used to predict the image of the two-dimensional anchor image through the continuous first element,
  • the shape constraint of the second element and the fixed texture of the specific area are used as input to predict the continuous animation image of the target object.
  • the selection module 503 is configured to dynamically select an animation matching the first animation from a plurality of preset animations as the background animation of the first animation while generating the first animation.
  • the background animation can be a variety of different types of background animation, for example, it can be serious, lively, happy, sad, and other different styles of animation.
  • the background animation has a certain length so that it can be called easily.
  • the background animation When calling the background animation, it is necessary to analyze the current scene of the input information, and based on the analysis result, dynamically select an animation that matches the current scene from a plurality of preset animations as the background animation. For example, if the analysis knows that the current input information is excited, then the excited background animation is called. When a change in the scene of the input information is detected, even if the currently called background animation has not been played, it will switch to call the background animation matching the changed scene. After the currently called background animation is played, if it is found that the current scene of the input information has not changed, the current background animation will continue to be played in a loop.
  • the generating module 504 is configured to generate a final animation related to the input information based on the first animation and the background animation.
  • the final animation related to the input information is generated.
  • the final animation can be stored or disseminated in the form of video files.
  • the background animation is switched. For this, it can be determined whether the background animation is composed of multiple different types of animation splicing, and if so, smooth processing is performed on the different types of animation. Make the transition between different types of animation more natural.
  • the device shown in FIG. 5 can correspondingly execute the content in the foregoing method embodiment.
  • an electronic device 60 which includes:
  • At least one processor and,
  • a memory communicatively connected with the at least one processor; wherein,
  • the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the animation generation method including the dynamic background in the foregoing method embodiment.
  • the embodiments of the present disclosure also provide a non-transitory computer-readable storage medium that stores computer instructions, and the computer instructions are used to make the computer execute the foregoing method embodiments.
  • the embodiments of the present disclosure also provide a computer program product, the computer program product includes a calculation program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, The computer executes the animation generation method including the dynamic background in the foregoing method embodiment.
  • FIG. 6 shows a schematic structural diagram of an electronic device 60 suitable for implementing embodiments of the present disclosure.
  • Electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablets), PMPs (portable multimedia players), vehicle-mounted terminals (for example, Mobile terminals such as car navigation terminals) and fixed terminals such as digital TVs, desktop computers, etc.
  • the electronic device shown in FIG. 6 is only an example, and should not bring any limitation to the function and scope of use of the embodiments of the present disclosure.
  • the electronic device 60 may include a processing device (such as a central processing unit, a graphics processor, etc.) 601, which may be loaded into a random access device according to a program stored in a read-only memory (ROM) 602 or from a storage device 608.
  • the program in the memory (RAM) 603 executes various appropriate actions and processing.
  • the RAM 603 also stores various programs and data required for the operation of the electronic device 60.
  • the processing device 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604.
  • An input/output (I/O) interface 605 is also connected to the bus 604.
  • the following devices can be connected to the I/O interface 605: including input devices 606 such as touch screen, touch panel, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; including, for example, liquid crystal display (LCD), speakers, An output device 607 such as a vibrator; a storage device 608 such as a magnetic tape, a hard disk, etc.; and a communication device 609.
  • the communication device 609 may allow the electronic device 60 to perform wireless or wired communication with other devices to exchange data.
  • the figure shows the electronic device 60 having various devices, it should be understood that it is not required to implement or have all the illustrated devices. It may alternatively be implemented or provided with more or fewer devices.
  • the process described above with reference to the flowchart can be implemented as a computer software program.
  • the embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart.
  • the computer program may be downloaded and installed from the network through the communication device 609, or installed from the storage device 608, or installed from the ROM602.
  • the processing device 601 the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.
  • the above-mentioned computer-readable medium in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two.
  • the computer-readable storage medium may be, for example, but not limited to, an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal propagated in a baseband or as a part of a carrier wave, and a computer-readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium.
  • the computer-readable signal medium may send, propagate, or transmit the program for use by or in combination with the instruction execution system, apparatus, or device .
  • the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to: wire, optical cable, RF (Radio Frequency), etc., or any suitable combination of the above.
  • the above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist alone without being assembled into the electronic device.
  • the above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains at least two Internet protocol addresses; and sends to the node evaluation device including the at least two A node evaluation request for an Internet Protocol address, wherein the node evaluation device selects an Internet Protocol address from the at least two Internet Protocol addresses and returns it; receives the Internet Protocol address returned by the node evaluation device; wherein, the obtained The Internet Protocol address indicates the edge node in the content distribution network.
  • the aforementioned computer-readable medium carries one or more programs, and when the aforementioned one or more programs are executed by the electronic device, the electronic device: receives a node evaluation request including at least two Internet Protocol addresses; Among the at least two Internet Protocol addresses, select an Internet Protocol address; return the selected Internet Protocol address; wherein, the received Internet Protocol address indicates an edge node in the content distribution network.
  • the computer program code used to perform the operations of the present disclosure may be written in one or more programming languages or a combination thereof.
  • the above-mentioned programming languages include object-oriented programming languages—such as Java, Smalltalk, C++, and also conventional Procedural programming language-such as "C" language or similar programming language.
  • the program code can be executed entirely on the user's computer, partly on the user's computer, executed as an independent software package, partly on the user's computer and partly executed on a remote computer, or entirely executed on the remote computer or server.
  • the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to pass Internet connection).
  • LAN local area network
  • WAN wide area network
  • each block in the flowchart or block diagram can represent a module, program segment, or part of code, and the module, program segment, or part of code contains one or more for realizing the specified logical function Executable instructions.
  • the functions marked in the block may also occur in a different order from the order marked in the drawings. For example, two blocks shown in succession can actually be executed substantially in parallel, or they can sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagram and/or flowchart, and the combination of the blocks in the block diagram and/or flowchart can be implemented by a dedicated hardware-based system that performs the specified functions or operations Or it can be realized by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments described in the present disclosure may be implemented in a software manner, or may be implemented in a hardware manner.
  • the name of the unit does not constitute a limitation on the unit itself under certain circumstances.
  • the first obtaining unit can also be described as "a unit for obtaining at least two Internet Protocol addresses.”

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Abstract

Les modes de réalisation de la présente invention concernent un procédé, un appareil et un dispositif électronique pour générer un arrière-plan dynamique contenant une animation, appartenant au domaine technique du traitement de données, ledit procédé consistant à: obtenir un modèle de reconstruction associé à une région spécifique et un premier élément et un second élément d'un objet cible; sur la base dudit modèle de reconstruction, déterminer une caractéristique de texture de la région spécifique associée à des informations d'entrée, et une action du premier élément et une action du second élément; tout en générant une première animation, sélectionner de manière dynamique, parmi une pluralité d'animations prédéfinies, une animation correspondant à ladite première animation devant être l'animation d'arrière-plan de la première animation; sur la base de la première animation et de ladite animation d'arrière-plan, générer une animation finale relative aux informations d'entrée. La solution de traitement de la présente invention augmente l'authenticité de l'image générée.
PCT/CN2020/074369 2019-03-20 2020-02-05 Procédé, appareil et dispositif électronique pour générer un arrière-plan dynamique contenant une animation WO2020186934A1 (fr)

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