Method and system for automatically generating shooting outline based on script

Abstract

The invention discloses a method and system for automatically generating a shooting outline based on a script, and the method comprises the steps: obtaining the script, and obtaining character paragraphs from the script; obtaining a character in a character paragraph in a shooting scene and performance information of the character; determining the emotion of the character according to the performance information; obtaining lens position information in the shooting scene; displaying the character, the performance information, the emotion and the lens position information in the shooting scene; and arranging all the shooting scenes displaying the thought, the performance information, the emotion and the lens position information in the script according to a time axis. According to the method and the device, the shooting script can be automatically generated, so that the time required by shooting personnel for reading and understanding the script is avoided, and a script basis is provided for improving the shooting efficiency to a certain extent.

Description

Technical Field

[0001] The present application relates to the field of software, and in particular, to a method and system for automatically generating a shooting outline based on a script. Background Art

[0002] The script is mainly composed of lines and stage instructions. It is the textual basis of theatrical art creation and the basis for the director and actors to perform. Words similar to scripts include scripts, plays, etc. It is a literary style that mainly expresses the plot in a representative manner. Scripts are mainly divided into literary scripts and photographic scripts. Literary scripts are scripts that highlight literary qualities and have a low sense of photography. They include drama scripts (or drama scripts), novel scripts (or drama novels), sketch scripts, crosstalk scripts, etc.; photographic scripts are scripts that highlight the sense of shooting. The literary and artistic quality can be high or low (determined by the film subject, market, investment funds, etc.), including scene scripts, storyboard scripts (storyboard scripts or movie scripts), scripts, etc. The script is one of the necessary tools for stage performances or filming. It is the reference language for the characters in the play to have dialogues. It is an art style that serves stage performances, which is different from drama and other literary styles.

[0003] Filmmakers generally shoot according to the script. However, shooting according to the script requires understanding it, and then manually splitting it according to their own ideas before shooting, which will affect the shooting efficiency to a certain extent. Summary of the invention

[0004] The embodiments of the present application provide a method and system for automatically generating a shooting outline based on a script, so as to at least solve the problem in the related art that the script needs to be understood during shooting, thereby affecting the shooting efficiency.

[0005] According to one aspect of the present application, a method for automatically generating a shooting outline based on a script is provided, which is applied to software, and the software is used to execute the method, and the method includes the following steps: obtaining a script and obtaining a text paragraph from the script; obtaining a character in the text paragraph in a shooting scene and the performance information of the character; wherein the performance information includes at least one of the following: language, action, expression; determining the emotion of the character according to the performance information; obtaining lens position information in the shooting scene, wherein the lens position information is used to indicate the relative position relationship between a camera or a virtual camera and the character when shooting the character, and the camera or the virtual camera is one or more; displaying the character, the performance information, the emotion and the lens position information in the shooting scene; arranging all the shooting scenes in the script that display the character, the performance information, the emotion and the lens position information according to the timeline.

[0006] Furthermore, obtaining the text paragraph from the script includes: dividing the script into different chapters according to the text in the script used to identify chapters; for each chapter, obtaining the corresponding scene in the chapter, wherein the scene is a shooting scene; and using the text in the same scene as the text paragraph.

[0007] Furthermore, it also includes: generating a corresponding two-dimensional coordinate system for each scene in all chapters of the script; arranging all the generated two-dimensional coordinate systems in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; displaying the arranged two-dimensional coordinate systems in the chapter; arranging all chapters in chronological order, and displaying the two-dimensional coordinate systems corresponding to all the arranged chapters.

[0008] Furthermore, determining the emotion of a character based on the performance information corresponding to a character includes: obtaining words in the performance information used to describe the character's actions and / or expressions, or obtaining the language of the character in the performance information, and obtaining words from the language used to indicate the character's emotions; dividing the words into positive words, neutral words and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second emotion, and the negative words correspond to a third emotion, and the first emotion, the second emotion and the third emotion are different emotions; determining the emotion of the character based on the words.

[0009] According to another aspect of the present application, a system for automatically generating a shooting outline based on a script is also provided, which is applied to software, and the software includes the following modules: an acquisition module, which is used to acquire a script and obtain a text paragraph from the script; a second acquisition module, which is used to acquire a character in a text paragraph in a shooting scene and the performance information of the character; wherein the performance information includes at least one of the following: language, action, expression; a determination module, which is used to determine the emotion of the character based on the performance information; a third acquisition module, which is used to acquire lens position information in the shooting scene, wherein the lens position information is used to indicate the relative position relationship between a camera or a virtual camera and the character when shooting the character, and the camera or the virtual camera is one or more; a display module, which is used to display the character, the performance information, the emotion and the lens position information in the shooting scene; a processing module, which is used to arrange all shooting scenes in the script that display the character, the performance information, the emotion and the lens position information according to a timeline.

[0010] Furthermore, the acquisition module is used to: divide the script into different chapters according to the text in the script used to identify chapters; obtain the corresponding scene in each chapter, wherein the scene is a shooting scene; and use the text in the same scene as the text paragraph.

[0011] Furthermore, the display module is also used to: generate a corresponding two-dimensional coordinate system for each scene in all chapters of the script; arrange all the generated two-dimensional coordinate systems in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; display the arranged two-dimensional coordinate systems in the chapter; arrange all chapters in chronological order, and display the two-dimensional coordinate systems corresponding to all the arranged chapters.

[0012] Furthermore, the determination module is used to: obtain words from the performance information for describing the character's actions and / or expressions, or obtain the language of the character in the performance information, and obtain words from the language for indicating the character's emotions; divide the words into positive words, neutral words, and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second emotion, and the negative words correspond to a third emotion, and the first emotion, the second emotion, and the third emotion are different emotions; determine the character's emotions based on the words.

[0013] According to another aspect of the present application, an electronic device is also provided, comprising a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the above-mentioned method steps.

[0014] According to another aspect of the present application, a readable storage medium is provided, on which computer instructions are stored, wherein the computer instructions implement the above method steps when executed by a processor.

[0015] In an embodiment of the present application, a script is obtained, and a text paragraph is obtained from the script; a character in a text paragraph under a shooting scene and the performance information of the character are obtained; wherein the performance information includes at least one of the following: language, action, expression; the emotion of the character is determined according to the performance information; the lens position information under the shooting scene is obtained, wherein the lens position information is used to indicate the relative position relationship between the camera or virtual camera and the character when shooting the character, and the camera or virtual camera is one or more; the character, the performance information, the emotion and the lens position information are displayed in the shooting scene; all the shooting scenes in the script that display the character, the performance information, the emotion and the lens position information are arranged according to the timeline. The shooting script can be automatically generated by this application, which avoids the time required for the shooting personnel to read and understand the script, and to a certain extent provides a script basis for improving shooting efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 is a flow chart of a method for automatically generating a shooting outline based on a script according to an embodiment of the present application;

[0018] Figure 2 is a schematic diagram of two-dimensional coordinates of emotional points according to an embodiment of the present application; and,

[0019] Figure 3 It is a schematic diagram of the two-dimensional coordinates of the emotion points of character A related to the event according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0022] In this embodiment, a complete shooting outline can be generated according to the script. This method can be called a method for automatically generating a shooting outline based on a script. Figure 1is a flow chart of a method for automatically generating a shooting outline based on a script according to an embodiment of the present application. Figure 1 As shown below, Figure 1 The steps involved in the process are described below.

[0023] Step S102, obtaining a script, and dividing the script into different chapters according to words used to indicate chapters in the script.

[0024] Step S104: for each chapter, obtain text paragraphs of different scenes in the chapter, wherein the scene is a shooting scene.

[0025] Step S106, obtaining a character in a text paragraph in a shooting scene and the character's performance information; wherein the performance information includes at least one of the following: language, action, and expression.

[0026] Step S108, determining the emotion of the character according to the performance information.

[0027] Step S110, obtaining lens position information in the shooting scene, wherein the lens position information is used to indicate the relative position relationship between the camera or virtual camera and the character when shooting the character, and the camera or virtual camera may be one or more.

[0028] As an optional implementation, the lens position information (or lens configuration) can be selected from pre-configured lens position information, wherein the pre-configured lens position information can be extracted from a multimedia file, and a machine learning model is trained using multiple sets of training data, each set of training data includes a photo or a video, and also includes the position information of the lens when the photo and video were taken; after training, all the current video clips can be input into the multimedia file, thereby generating a variety of lens position information. The generated lens position information is linked to the preview of the video clip, so that all previews are provided for the user to select the appropriate lens position information.

[0029] Step S112, displaying the character, the performance information, the emotion and the camera position information in the shooting scene.

[0030] Step S114, arranging all the shooting scenes in the script that display the thoughts, the performance information, the emotions and the lens position information according to the time axis.

[0031] Step S116, generating a table of the arranged shooting scenes, wherein the columns of the table are different shooting scenes, and the multiple rows under the columns are the characters in the shooting scene, the performance information of the characters, the emotions of the characters and the camera position information.

[0032] The shooting script can be automatically generated through the above steps, which avoids the time required for the shooting personnel to read and understand the script, and to a certain extent provides a script basis for improving the shooting efficiency.

[0033] The generated shooting script may be in a table format, and the header content of the table may be as follows:

[0034]

[0035] The options in each of the above tables can also be referred to as sections. Preset section information can be obtained, wherein the section information includes: user-defined sections, wherein the customized sections include: character relationship sections, contradiction sections, time sections, scene sections, and sequence sections; an outline is generated according to the preset section information, and according to the outline, the user modifies and confirms the generation of a story line, and fills in the story outline according to the story line, and the user modifies and confirms the generation of a table. Among them, the relationship network includes: character relationship sections and contradiction sections; the basic framework includes: sequence sections, scene sections, and time sections; after the outline is generated, the user checks whether it conforms to his or her ideas. If not, the outline is modified; if it conforms, a story line is generated according to the outline. Fill in the content according to the story line to generate a story outline; if not, the story outline is modified; if it conforms, a table diagram is generated according to the story outline.

[0036] The quality of a film or TV work depends largely on whether the story is attractive, which requires sufficient conflicts in the film script. At present, the evaluation of the amount of conflict in a film script mainly depends on people's subjective reading. This depends on people's subjective factors and cannot objectively measure the script. That is, there is no solution in the relevant technology that can objectively display the amount of conflict.

[0037] Scripts, especially those used for filming TV dramas, need to be presented to the audience in the form of images. The conflicts felt by the audience are basically expressed through the actors' performances of their roles. Therefore, the following implementation methods objectively present the emotional changes of the characters in the script, so that film and television workers can clearly and objectively evaluate whether the conflict in a certain scene in a script is sufficient, providing an objective basis for script modification and even subsequent filming.

[0038] In the following implementation, a method for determining the frequency of dramatic conflict based on a script is provided, which is applied to software, and the software is used to execute the method. The steps included in the method are described below.

[0039] Obtain a text paragraph from a script, wherein the text paragraph is a text paragraph under the same shooting scene, and the text paragraph describes at least one character and the performance information corresponding to the character, wherein the performance information includes at least one of the following: language, action, and expression. Determine the emotion of a character according to the performance information corresponding to the character, wherein the emotion is determined according to the text description in the performance information, and the emotion is several preset emotions. Obtain a timeline corresponding to the performance information, and arrange the emotions of the character in a two-dimensional coordinate system according to the time order on the timeline; wherein the horizontal axis of the two-dimensional coordinate system is the timeline, and the vertical axis of the two-dimensional coordinate system is the emotion, and different emotions have different positions on the vertical axis. The two-dimensional coordinate system is displayed, wherein the displayed two-dimensional coordinate system is used as a shooting outline, and the emotions on the two-dimensional coordinate system are used as the basis for determining the dramatic conflict in the scene. Each emotion in the two-dimensional coordinate system is mapped to a value on the vertical axis, and the closer the position on the vertical axis is to the origin of the coordinate system, the lower the emotion corresponding to the value on the vertical axis, and the farther away from the origin of the coordinate system, the higher the emotion corresponding to the value on the vertical axis. Each emotion corresponds to a point on the two-dimensional coordinate system.

[0040] In an additional implementation, the points corresponding to the emotions displayed in the two-dimensional coordinate system can be connected to form a curve, which can be called an emotion curve; the curve is compared with a pre-configured curve, and if the similarity between the curve and the pre-configured curve exceeds a threshold, it is determined that the scene corresponding to the curve meets the requirements. The pre-configured curve can be generated based on the emotions in the scene in the script selected by the expert; the script selected by the expert can be some classic and excellent scripts.

[0041] Through the above steps, the problem of subjective script evaluation caused by the inability to objectively display the conflicts in the script in the related technology is solved, so that the emotional changes in the script can be objectively displayed, providing objective data for evaluating the prominence in the script.

[0042] Usually a script may also include different chapters. In order to distinguish chapters, in an optional implementation, obtaining the text paragraphs from the script may include the following steps: dividing the script into different chapters according to the text in the script used to identify chapters; for each chapter, respectively obtaining the corresponding scene in the chapter, wherein the scene is a shooting scene; and using the text in the same scene as the text paragraph.

[0043] Corresponding to each chapter, in an optional implementation, a corresponding two-dimensional coordinate system is generated for each scene in all chapters of the script; all generated two-dimensional coordinate systems are arranged in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; the arranged two-dimensional coordinate systems are displayed in the chapter; all chapters are arranged in chronological order, and the two-dimensional coordinate systems corresponding to all arranged chapters are displayed.

[0044] There are many methods for determining emotions. For example, the following method for determining emotions can also be applied to this embodiment. The method is described in detail below.

[0045] Obtain the text to be evaluated of the customer service to be evaluated. The text to be evaluated includes the audio text of the interaction between the customer service to be evaluated and different users in different service scenarios. The audio text is the text obtained after voice translation of the corresponding audio data. In this step, multiple different service scenarios are set for the customer service, and each service scenario is set with a corresponding service dialogue. The text to be evaluated is obtained by respectively obtaining the audio text of the interaction between the customer service to be evaluated and different users in different service scenarios. Optionally, in this step, the customer service number of the customer service to be evaluated can be matched with the service database to obtain the text to be evaluated of the customer service to be evaluated. The service database stores the corresponding relationship between different customer service numbers and the corresponding text to be evaluated. The audio text in the text to be evaluated is input into the pre-trained sentiment analysis model for sentiment analysis to obtain the text sentiment value. The emotion analysis model may adopt a network structure such as a deep learning model, a generative adversarial network or a recurrent neural network. Optionally, in this step, before the audio text in the text to be evaluated is input into the pre-trained emotion analysis model for emotion analysis, the step includes: constructing an emotion dictionary, and respectively annotating multiple sample audio texts according to the emotion dictionary to obtain sample annotation information corresponding to each sample audio text; wherein the emotion dictionary stores a mapping relationship between different words and information such as emotion intensity, emotion type, part of speech type and polarity, wherein the polarity is used to characterize the degree of positive or negative opinion of the user, and the sample annotation information includes the emotion intensity and emotion type corresponding to the sample audio text; the sample annotation information is normalized to generate standard sample annotation information; wherein the normalization is used to map the emotion intensity in the sample annotation information to a preset range. In this step, the emotion intensity corresponding to the positive emotion in the sample annotation information is mapped to [0, 1], and the emotion intensity corresponding to all negative emotions is mapped to [-1, 0], where 0 represents neutral emotion, so as to achieve the effect of normalizing the sample annotation information and obtain the standard sample annotation information. According to the multiple sample audio texts and the standard sample annotation information corresponding to each sample audio text, the emotion analysis model is trained until the emotion analysis model converges to obtain the pre-trained emotion analysis model; wherein, in this step, the emotion analysis model adopts a deep learning model, and the multiple sample audio texts are input into the deep learning model for emotion analysis to obtain emotion results, and the model loss value of the deep learning model is calculated according to the emotion results and the sample annotation information, and the parameters in the deep learning model are updated by using the stochastic gradient descent method (Stachastic gradient desent, SGD), until the number of iterations of the deep learning model is greater than the number threshold, or the output model loss value is less than the loss threshold, the emotion analysis model is judged to be converged, and the text emotion value corresponding to the input audio file can be effectively calculated based on the converged emotion analysis model.

[0046] The text emotion value of the audio text corresponding to different users in the same service scenario in the text to be evaluated is determined as the first emotion value, and the text emotion value of the audio text corresponding to the same user in different service scenarios in the text to be evaluated is determined as the second emotion value. Among them, there can be one or more audio texts corresponding to different users in the same service scenario. If there is one audio text, the text emotion value of the audio text is determined as the first emotion value. If there are multiple, one can be selected, such as randomly selecting an audio text, and the text emotion value of the selected audio text is determined as the first emotion value, or the average value of the text emotion value between the audio texts corresponding to the same user is calculated to obtain the first emotion value. In this step, there can be one or more audio texts corresponding to the same user in different service scenarios. If there is one audio text, the text emotion value of the audio text is determined as the second emotion value. If there are multiple, one can be selected, such as randomly selecting an audio text, and the text emotion value of the selected audio text is determined as the first emotion value, or the average value of the text emotion value between the audio texts corresponding to the same user in the corresponding service scenario is calculated to obtain the second emotion value. Optionally, in this step, the text emotion value of the audio texts corresponding to different users in the text to be evaluated in the same service scenario is determined as the first emotion value, and the text emotion value of the audio texts corresponding to the same user in different service scenarios in the text to be evaluated is determined as the second emotion value, including: determining the audio texts corresponding to different users in the text to be evaluated in the same service scenario as the first evaluation text, and determining the average value of the text emotion values ​​between the audio texts in the first evaluation text to obtain the first emotion value; wherein, by determining the audio texts corresponding to different users in the text to be evaluated in the same service scenario as the first evaluation text, all the audio texts between different users in the same service scenario can be effectively obtained, and based on the first emotion value corresponding to the first evaluation text, the average value of the satisfaction between different users in the same service scenario can be effectively represented; based on the average value of the satisfaction between different users in the same service scenario, the service effect of the customer service to be evaluated on different users in the same service scenario can be effectively evaluated; for example, for service scenario A, when the first emotion value is larger, it is determined that the service effect of the customer service to be evaluated on the user in service scenario A is better, and the user satisfaction is higher.The audio text corresponding to the same user in different service scenarios in the text to be evaluated is determined as the second evaluation text, and the average value of the text emotion values ​​between the audio texts in the second evaluation text is determined to obtain the second emotion value; wherein, by determining the audio text corresponding to the same user in different service scenarios in the text to be evaluated as the second evaluation text, the audio text of the same user in different service scenarios can be effectively obtained, and based on the second emotion value corresponding to the second evaluation text, the average value of the corresponding user satisfaction in different service scenarios can be effectively represented; based on the average value of the corresponding user satisfaction in different service scenarios, the service effect of the customer service to be evaluated on the same user in different service scenarios can be effectively evaluated.

[0047] In another example, a method for emotion recognition on Weibo is provided, which can also be applied to the present embodiment. The method includes: constructing a vocabulary list of a case Weibo comment corpus: collecting case Weibo comment text as an experimental data set, and performing data preprocessing such as deleting meaningless characters, word segmentation, and part-of-speech tagging to obtain a vocabulary list of a case Weibo comment corpus; constructing a basic emotion dictionary: based on the emotion vocabulary ontology of Dalian University of Technology, using its seven emotion categories of joy, good, anger, sorrow, fear, evil, and surprise, a basic emotion dictionary is constructed; by sorting out existing emotion computing resources, emoticons and Internet buzzwords commonly used on Weibo are collected and classified to obtain a negation dictionary, a degree adverb dictionary, an emoticon set, and an Internet buzzword set; constructing a seed emotion word set: using all words that appear in the case Weibo comment corpus vocabulary list of the basic emotion dictionary as seeds Emotional words constitute the seed emotion word set; construct the case microblog emotion dictionary: first, use the SO-PMI (semantic-oriented point mutual information) algorithm to mine candidate emotion words of 7 emotion categories in the word list of the case microblog comment corpus; then, by calculating the cosine similarity of the word vectors of the candidate emotion words of each category and the seed emotion words of the corresponding category, retain the candidate emotion words with an average cosine similarity greater than 0.5 as the case microblog emotion new words of the corresponding category to form an extended emotion dictionary; then, manually screen the extended emotion words and add them to the seed emotion word set, perform incremental iteration to mine new domain emotion words; finally, stop the iteration when the algorithm cannot mine new emotion words, integrate the extended emotion dictionary and the basic emotion dictionary to obtain the case microblog emotion dictionary. As a preferred solution of the present invention, the SO-PMI algorithm first screens out all words in the word list of the case microblog comment corpus with the following parts of speech: adjective, verb, noun, adverb and emoticon part of speech "emoji", where the emoticon part of speech "emoji" is a manually defined tag for emoticon words; then calculates the SO-PMI value between each word and all emotional words in each emotional category in the seed emotional word set, and retains the words with SO-PMI values ​​greater than zero as candidate emotional words of the corresponding category. The SO-PMI value of the word is greater than zero and the larger the value, the more relevant the word is to the current emotional category. All resources are integrated into a case microblog emotional knowledge base including a case microblog emotional dictionary, a negation dictionary, a degree adverb dictionary, an emoticon set and a network buzzword set; the part of speech and emotional label attribute features of words are defined using the case microblog emotional knowledge base, and the attribute feature representation of case microblog comments is constructed. The semantic representation and attribute feature representation of the comment are fused through a dual-channel convolutional neural network, and the emotional classifier of the comment is trained. A dual-channel convolutional neural network model is constructed to fuse the case microblog emotional knowledge, and the emotional classification of the case microblog comments is realized. The semantic representation of case microblog comments is a process of segmenting the comment sentences, and then querying and assigning word vectors to each word by loading the pre-trained word vector list WN×d.

[0048] The attribute feature representation of microblog comments is a process of constructing an attribute feature representation matrix based on a sparse binary vector representation method; first, K types of part-of-speech and sentiment label attributes are defined for each word; then, for a given comment text sequence T = {w1, w2, ..., wn} containing n words, each word wi is mapped to a K-dimensional Boolean binary vector vbool_i through part-of-speech tagging and querying the case microblog sentiment knowledge base. The value of each dimension of vbool_i is 0 / 1, 0 means that the feature is not present, and 1 means that the feature is present. The dual-channel convolutional neural network uses INIT-CNN as a benchmark method to construct a dual-channel convolutional neural network model; among them, INIT-CNN is a text classification model constructed based on convolutional neural networks and using an initialized convolution filter technology. After constructing the semantic representation and attribute feature representation of the comments, they are input into a dual-channel convolutional neural network together to extract deep semantic features and emotional knowledge features; then these two features are directly concatenated to obtain semantic synthesis features; finally, the semantic synthesis features are input into the fully connected layer for linear transformation and dimensionality reduction, and then the classification category probability distribution of each input text is output through the Softmax layer.

[0049] In this embodiment, an optional method is also provided, which determines the emotion of a character according to the performance information corresponding to the character, including: obtaining words used to describe the character's actions and / or expressions in the performance information, or obtaining the language of the character in the performance information, and obtaining words used to indicate the character's emotions from the language; dividing the words into positive words, neutral words and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second emotion, and the negative words correspond to a third emotion, and the first emotion, the second emotion and the third emotion are different emotions; and determining the emotion of the character according to the words.

[0050] All emotion allocations may include the above three emotions. Of course, in addition to the above three emotions, multiple emotions may also be included. The classification of emotion types may be set as needed, but no matter how it is set, it should include the above three emotions, namely the first emotion, the second emotion and the third emotion.

[0051] Figure 2 is a schematic diagram of two-dimensional coordinates of emotional points according to an embodiment of the present application, such as Figure 2 As shown in the figure, there can be four values ​​on the vertical axis, and the time on the horizontal axis is in units of 30 seconds. The points on the two-dimensional coordinates can be connected to form an emotion curve. An emotion curve can be generated for each character. The current event read from the script can also be marked on the points on the emotion curve of a character, so that the reason for the change of the emotion curve can be more clearly shown. Figure 3is a schematic diagram of two-dimensional coordinates of emotional points of character A related to events according to an embodiment of the present application, such as Figure 3 As shown, the emotional changes of character A are written out from the script. After being drawn into a two-dimensional coordinate system, events related to the emotional changes of character A are read out from the script and displayed on the two-dimensional coordinate system, thereby making the two-dimensional coordinate system more intuitive.

[0052] As an additional implementation method, the frequency of emotion changes can also be determined to determine whether the dramatic conflict in the scene is sufficient. That is, the implementation method can also include the following steps: obtaining a two-dimensional coordinate system in a scene; obtaining all emotions in the two-dimensional coordinate system, and determining the number of times the emotion changes on the time axis, wherein the change is the change between the first emotion, the second emotion, and the third emotion; obtaining the duration of the scene when it is filmed into a video; determining the frequency of emotion changes based on the duration and the number; and displaying the two-dimensional coordinate system using different colors, wherein different change frequencies correspond to different colors.

[0053] As another implementation that can be added, when the frequency of change of the emotion is lower than a first threshold or the frequency of change of the emotion is higher than a second threshold, a prompt message is displayed, wherein the prompt message is used to indicate that the frequency of change of the emotion is too slow or too fast.

[0054] The above implementation solves the problem of subjective script evaluation caused by the inability to objectively display the conflicts in the script in the related art, thereby being able to objectively display the emotional changes in the script and providing objective data for evaluating the highlights in the script.

[0055] In this embodiment, an electronic device is provided, including a memory and a processor. The memory stores a computer program, and the processor is configured to run the computer program to execute the method in the above embodiment.

[0056] The above program can be run in the processor, or it can also be stored in the memory (or computer-readable medium), which includes permanent and non-permanent, removable and non-removable media. Information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, modules of programs 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, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape 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.

[0057] These computer programs can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps of the functions specified in one or more blocks can be implemented by different modules corresponding to different steps.

[0058] Such a device or system is provided in this embodiment. The system is called a system for automatically generating a shooting outline based on a script, and is applied to software, which includes the following modules: an acquisition module, which is used to acquire a script and obtain a text paragraph from the script; a second acquisition module, which is used to acquire a character in a text paragraph under a shooting scene and the performance information of the character; wherein the performance information includes at least one of the following: language, action, expression; a determination module, which is used to determine the emotion of the character according to the performance information; a third acquisition module, which is used to acquire the lens position information under the shooting scene, wherein the lens position information is used to indicate the relative position relationship between the camera or virtual camera and the character when shooting the character, and the camera or virtual camera is one or more; a display module, which is used to display the character, the performance information, the emotion and the lens position information under the shooting scene; a processing module, which is used to arrange all the shooting scenes in the script that display the character, the performance information, the emotion and the lens position information according to the timeline.

[0059] The system or device is used to implement the functions of the method in the above-mentioned embodiment. Each module in the system or device corresponds to each step in the method, which has been explained in the method and will not be repeated here.

[0060] Optionally, the acquisition module is used to: divide the script into different chapters according to the text in the script used to identify chapters; for each chapter, respectively acquire the corresponding scene in the chapter, wherein the scene is a shooting scene; and use the text in the same scene as the text paragraph.

[0061] Optionally, the display module is also used to: generate a corresponding two-dimensional coordinate system for each scene in all chapters of the script; arrange all the generated two-dimensional coordinate systems in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; display the arranged two-dimensional coordinate systems in the chapter; arrange all chapters in chronological order, and display the two-dimensional coordinate systems corresponding to all the arranged chapters.

[0062] Optionally, the determination module is used to: obtain words from the performance information for describing the character's actions and / or expressions, or obtain the language of the character in the performance information, and obtain words from the language for indicating the character's emotions; divide the words into positive words, neutral words, and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second emotion, and the negative words correspond to a third emotion, and the first emotion, the second emotion, and the third emotion are different emotions; determine the character's emotions based on the words.

[0063] Optionally, the determination module is also used to: obtain a two-dimensional coordinate system in a scene; obtain all emotions in the two-dimensional coordinate system, and determine the number of times the emotion changes on the timeline, wherein the change is the change between the first emotion, the second emotion and the third emotion; obtain the duration of the scene when it is captured as a video; determine the frequency of change of the emotion based on the duration and the number of times; and display the two-dimensional coordinate system using different colors, wherein different change frequencies correspond to different colors.

[0064] As another implementation that can be added, the display module is also used to: when the frequency of change of the emotion is lower than a first threshold or the frequency of change of the emotion is higher than a second threshold, display a prompt message, wherein the prompt message is used to indicate that the frequency of change of the emotion is too slow or too fast.

[0065] Through the above implementation, the problem of subjective script evaluation caused by the inability to objectively display the conflicts in the script in the related art is solved, so that the emotional changes in the script can be objectively displayed, providing objective data for evaluating the highlights in the script.

[0066] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for automatically generating a shooting outline based on a script, applied to software, wherein the software is used to execute the method, characterized in that: The method comprises the following steps: Obtaining a script and obtaining text passages from the script; Obtaining a character in a text paragraph in a shooting scene and performance information of the character; wherein the performance information includes at least one of the following: language, action, expression; determining the emotion of the character according to the performance information; Acquire lens position information in the shooting scene, wherein the lens position information is used to indicate a relative position relationship between a camera or a virtual camera and the person when shooting the person, and the camera or the virtual camera may be one or more; Displaying the character, the performance information, the emotion and the camera position information under the shooting scene; All the shooting scenes in the script showing the thoughts, the performance information, the emotions and the lens position information are arranged according to the time axis and displayed after the arrangement.

2. The method according to claim 1, characterized in that Obtaining the text paragraph from the script includes: Dividing the script into different chapters according to the characters used to identify the chapters in the script; For each chapter, respectively obtain a corresponding scene in the chapter, wherein the scene is a shooting scene; The text in the same scene is regarded as the text paragraph.

3. The method according to claim 2, characterized in that Also includes: Generate a corresponding two-dimensional coordinate system for each scene in all chapters of the script; Arrange all generated two-dimensional coordinate systems in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; The arranged two-dimensional coordinate system is displayed in this section; Arrange all chapters in chronological order, and display the two-dimensional coordinate system corresponding to all the arranged chapters.

4. The method according to any one of claims 1 to 3, characterized in that Determining the emotion of a character according to performance information corresponding to the character includes: Acquire words used to describe the action and / or expression of the character in the performance information, or acquire the language of the character in the performance information, and acquire words used to indicate the emotion of the character from the language; Classifying the words into positive words, neutral words and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second word, and the negative words correspond to a third emotion, and the first emotion, the second emotion and the third emotion are different emotions; An emotion of the character is determined based on the words.

5. A system for automatically generating a shooting outline based on a script, applied to software, characterized in that: The software includes the following modules: An acquisition module, used to acquire a script and obtain text paragraphs from the script; The second acquisition module is used to acquire a character in a text paragraph in a shooting scene and the performance information of the character; wherein the performance information includes at least one of the following: language, action, expression; A determination module, used to determine the emotion of the character according to the performance information; A third acquisition module is used to acquire lens position information in the shooting scene, wherein the lens position information is used to indicate the relative position relationship between the camera or virtual camera and the person when shooting the person, and the camera or virtual camera may be one or more; A display module, used to display the character, the performance information, the emotion and the camera position information in the shooting scene; The processing module is used to arrange all the shooting scenes in the script that display the thoughts, the performance information, the emotions and the lens position information according to the time axis, and display them after arrangement.

6. The system according to claim 5, characterized in that The acquisition module is used for: Dividing the script into different chapters according to the characters used to identify the chapters in the script; For each chapter, respectively obtain a corresponding scene in the chapter, wherein the scene is a shooting scene; The text in the same scene is regarded as the text paragraph.

7. The system according to claim 6, characterized in that The display module is also used for: Generate a corresponding two-dimensional coordinate system for each scene in all chapters of the script; Arrange all generated two-dimensional coordinate systems in chronological order according to the scenes corresponding to the two-dimensional coordinate systems in the chapter; The arranged two-dimensional coordinate system is displayed in this section; Arrange all chapters in chronological order, and display the two-dimensional coordinate system corresponding to all the arranged chapters.

8. The system according to any one of claims 5 to 7, characterized in that The determination module is used for: Acquire words used to describe the action and / or expression of the character in the performance information, or acquire the language of the character in the performance information, and acquire words used to indicate the emotion of the character from the language; Classifying the words into positive words, neutral words and negative words, wherein the positive words correspond to a first emotion, the neutral words correspond to a second word, and the negative words correspond to a third emotion, and the first emotion, the second emotion and the third emotion are different emotions; An emotion of the character is determined based on the words.

9. An electronic device comprising a memory and a processor; wherein: The memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps described in any one of claims 1 to 4.

10. A readable storage medium having computer instructions stored thereon, wherein: When the computer instructions are executed by a processor, the method steps described in any one of claims 1 to 4 are implemented.

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