Information processing method, device and readable storage medium

Abstract

This application discloses an information processing method, device, and readable storage medium, relating to the field of computer technology, for enhancing the realism of a virtual avatar's movements. The method comprises: obtaining a first skeletal point position relationship of a user's actual movements; obtaining an adjustment parameter; obtaining a second skeletal point position relationship of the user's virtual avatar based on the adjustment parameter and the first skeletal point position relationship; and displaying the virtual avatar based on the second skeletal point position relationship. The adjustment parameter is determined based on one or more of the following information: temperature information and information about the display device used to display the virtual avatar. Embodiments of this application can enhance the realism of a virtual avatar's movements.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an information processing method, device, and readable storage medium. Background Art

[0002] Cloud gaming, based on cloud computing technology, allows more players to enjoy high-quality gaming experiences. For ice and snow-themed motion-sensing games, users have higher expectations for the gaming experience and demand a more realistic experience.

[0003] Existing ice and snow motion-sensing games can immerse users in the action and significantly reduce weather and venue restrictions. However, these existing ice and snow motion-sensing cloud games simply present corresponding virtual characters based on the user's movements, resulting in a poor gaming experience. Therefore, solving this problem is a major research topic for those skilled in the art. Summary of the Invention

[0004] The embodiments of the present application provide an information processing method, device, and readable storage medium to improve user experience.

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

[0006] Get the position relationship of the first skeleton point of the user's actual action;

[0007] Get adjustment parameters;

[0008] Obtaining a second skeleton point position relationship of the user's virtual image based on the adjustment parameter and the first skeleton point position relationship;

[0009] displaying the virtual image according to the positional relationship of the second skeleton points;

[0010] The adjustment parameter is determined based on one or more of the following information:

[0011] Temperature information and information of a display device for displaying the virtual image.

[0012] In a second aspect, an embodiment of the present application further provides an information processing device, including:

[0013] A first acquisition module is used to obtain the position relationship of the first skeleton point of the user's actual action;

[0014] A second acquisition module is used to obtain adjustment parameters;

[0015] a first adjustment module, configured to obtain a second skeletal point position relationship of the user's virtual image based on the adjustment parameter and the first skeletal point position relationship;

[0016] a first display module, configured to display the virtual image according to the positional relationship of the second skeletal points;

[0017] The adjustment parameter is determined based on one or more of the following information:

[0018] Temperature information and information of a display device for displaying the virtual image.

[0019] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements the steps of the information processing method described above when executing the program.

[0020] In a fourth aspect, an embodiment of the present application further provides a readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in the information processing method described above are implemented.

[0021] In an embodiment of the present application, the obtained adjustment parameters are used to adjust the first skeletal point position relationship of the user's current actual action, and the second skeletal point position relationship of the virtual image is obtained and displayed. The adjustment parameters include temperature information and information of the display device used to display the virtual image. Since the adjustment parameters obtained in the embodiment of the present application take into account the influence of temperature information on the skeletal point position relationship and / or the influence of the display device information on the skeletal point position relationship, the solution of the embodiment of the present application can be used to present a virtual image with different actions according to the user's actual action under different temperatures and / or different display device information, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is one of the flow charts of the information processing method provided in the embodiment of the present application;

[0023] Figure 2 This is a schematic diagram of the human body according to the skeletal nodes provided in an embodiment of the present application;

[0024] Figure 3(a) shows the captured image of the user’s actual action;

[0025] Figure 3(b) is the obtained skeleton point position relationship diagram;

[0026] Figure 4 A schematic diagram of the positional relationship of the skeleton points of the virtual image in the embodiment of the present application;

[0027] Figure 5 It is a structural diagram of the information processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In the embodiments of this application, the term "and / or" describes the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0029] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0030] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0031] See also Figure 1 , Figure 1 is a flow chart of the information processing method provided in the embodiment of the present application, such as Figure 1 As shown, the following steps are included:

[0032] Step 101: Obtain the position relationship of the first skeleton point of the user's actual action.

[0033] Specifically, in this step, multiple consecutive frames of images of the actual action may be acquired. Detection frames are then determined from these multiple frames based on a preset interval, and the image between two consecutive detection frames is used as a tracking frame. Skeletal point detection results in the detection frames and skeletal point tracking results in the tracking frames are then acquired, and the first skeletal point positional relationship is determined based on these skeletal point detection and tracking results. The preset interval can be set as needed.

[0034] The solution of the embodiment of the present application can be applied to ice and snow somatosensory cloud game scenes. Among them, the actual action of the user refers to the real action currently displayed by the user. Specifically, an image sequence of the object to be detected (that is, the actual action of the user or the user) is obtained, and the image sequence includes multiple consecutive frames of images. The detection frame is determined from the image sequence according to the preset frame interval. For example, 20 consecutive frames of images are obtained, and the serial numbers are marked as {0, 1, 2, ... 19} respectively. The preset frame interval is 3, then the serial numbers of the detection frames are {0, 4, 8, 12, 16}. The image frames between two adjacent detection frames are tracking frames. In the detection frame, the skeleton point detection result of the detection frame is obtained. Based on the skeleton point detection result in the detection frame, the skeleton point tracking result of each tracking frame is obtained by optical flow calculation. Afterwards, the final detection result is determined based on the skeleton point detection result and the skeleton point tracking result. For example, the skeleton point tracking result in the tracking frame is used to correct the skeleton point detection result or skeleton point tracking result obtained in the previous frame. In this way, since the skeleton point tracking result in the tracking frame and the skeleton point detection result in the detection frame can be used to correct the skeleton point tracking result, the accuracy of the obtained first skeleton point position relationship can be improved.

[0035] like Figure 2 As shown, the human body is labeled with information capture nodes based on the skeletal nodes. The information capture nodes are numbered from bottom to top as {head: A, neck: B, right shoulder: C, left shoulder: D, right elbow: E, left elbow: F, right wrist: G, left wrist: H, right hip: I, left hip: J, pelvis: K, right knee: L, left knee: M, right ankle: N, left ankle: O}, i.e., 15 information capture nodes. By using these information capture nodes, the positional relationships between these nodes are obtained, which in turn yields the positional relationships of the skeletal points. Figure 3(a) shows the captured image of the user's actual movements; Figure 3(b) shows the obtained skeletal point positional relationships.

[0036] Step 102: Obtain adjustment parameters.

[0037] The adjustment parameter is determined based on one or more of the following information:

[0038] Temperature information and information of a display device for displaying the virtual image.

[0039] The temperature information includes temperature information corresponding to the actual action, which can be set as needed, for example, to the temperature of the actual environment in which the user is performing the actual action, or to the temperature the user expects to experience in the game, etc. Information about the display device used to display the virtual image, including the resolution of the display device, etc.

[0040] There are different ways to obtain the adjustment parameters according to different adjustment parameters:

[0041] For example, when the adjustment parameter is temperature information, the target action type of the actual action is obtained, and then the first adjustment parameter corresponding to the target action type is determined according to the temperature information corresponding to the actual action, and the first adjustment parameter is used as the adjustment parameter.

[0042] For another example, when the adjustment parameter is information of a display device used to display the virtual image, in this step, the target action type of the actual action is obtained, and based on the resolution of the display device used to display the virtual image, the second adjustment parameter corresponding to the target action type is determined, and the second adjustment parameter is used as the adjustment parameter.

[0043] For another example, when the adjustment parameters include temperature information and information about the display device used to display the virtual image, in this step, the target action type of the actual action is obtained. Subsequently, a first adjustment parameter corresponding to the target action type is determined based on the temperature information corresponding to the actual action; and a second adjustment parameter corresponding to the target action type is determined based on the resolution of the display device used to display the virtual image. Finally, the first adjustment parameter and the second adjustment parameter are used to obtain the adjustment parameter corresponding to the target action type. For example, the product of the first adjustment parameter and the second adjustment parameter can be used as the adjustment parameter corresponding to the target action type.

[0044] The action type may include acceleration action, jumping action, turning action, etc. The target action type is one of the above action types.

[0045] In the above cases, when the target action type is an acceleration action or a jump action, the difference between the temperature value of the temperature information corresponding to the actual action and a preset temperature threshold is calculated; the first absolute value of the quotient of the difference and the preset temperature threshold is calculated; and the absolute value of the difference between the reference value and the first absolute value is used as the first adjustment parameter. The reference value can be 1.

[0046] Specifically,

[0047] Wherein, α represents the first adjustment parameter when the target action type is an acceleration action, and t represents the temperature value of the temperature information corresponding to the actual action. Here, the preset temperature threshold is 26 and the reference value is 1.

[0048] Specifically,

[0049] Wherein, β represents the first adjustment parameter when the target action type is a jump action, t represents the temperature value of the temperature information corresponding to the actual action, and here, the preset temperature threshold is 26 and the reference value is 1.

[0050] In the above cases, when the target action type is a turning action, the difference between the temperature value of the temperature information corresponding to the actual action and a preset temperature threshold is calculated; the second absolute value of the quotient of the difference and the preset temperature threshold is calculated; and the absolute value of the sum of the reference value and the second absolute value is used as the first adjustment parameter. The reference value can be 1.

[0051] Specifically,

[0052] Wherein, γ represents the first adjustment parameter when the target action type is a turning action, and t represents the temperature value of the temperature information corresponding to the actual action. Here, the preset temperature threshold is 26 and the reference value is 1.

[0053] In the above cases, when the resolution is greater than the first preset value, the value of the second adjustment parameter is determined to be 1; when the resolution is less than or equal to the first preset value, the second adjustment parameter is the quotient of the product of the first coefficient and the second coefficient and the resolution; wherein the first coefficient and the second coefficient are greater than 0. The first coefficient and the second coefficient can be set as needed. For example, the first coefficient is set to 3840 and the second coefficient is set to 2160.

[0054] The first preset value can be set to 4K. For resolutions of 4K and above, δ=1; for resolutions lower than 4K, δ represents the second adjustment parameter.

[0055] Then, based on the above examples, when the adjustment parameters include temperature information and information of the display device used to display the virtual image:

[0056] When the target action type is an acceleration action, the adjustment parameter Δ1 = α·δ; when the target action type is a jumping action, the adjustment parameter Δ2 = β·δ; when the target action type is a turning action, the adjustment parameter Δ3 = γ·δ.

[0057] In this way, different adjustment parameters are obtained by combining different action types, so that the actions of the user's virtual image and the user's actual actions are more consistent.

[0058] Step 103: Obtain a second skeleton point position relationship of the user's virtual image based on the adjustment parameter and the first skeleton point position relationship.

[0059] Specifically, in this step, a first angle between a first target skeletal point and a second target skeletal point is obtained from the first skeletal point positional relationship. Subsequently, the product of the first angle and the adjustment parameter is used as a second angle between the first target skeletal point and the second target skeletal point, and the second angle is used to form a second skeletal point positional relationship for the avatar.

[0060] Combine Figure 2 As shown, the first angle may include: ∠ABC, ∠ABD, ∠ABK, ∠BCE, ∠CEG, ∠BDF, ∠DFH, ∠BKI, ∠BKJ, ∠KIJ, ∠KJM, ∠ILN, ∠JMO. Then, for the adjustment parameter calculated in step 102, each angle is multiplied by the obtained adjustment parameter to obtain the second angle of the second target skeleton point, and the second skeleton point position relationship of the user's avatar is obtained, that is, the information capture node angle (i.e., the skeleton point position relationship) of the final avatar in the game is obtained.

[0061] For example, according to the position relationship of the skeleton points in step 101, the game temperature is -15°C, and the resolution of the display terminal screen is 720P, the following is obtained: Figure 4 The position relationship of the skeleton points of the virtual image in the game screen is shown.

[0062] Step 104: Display the virtual image according to the positional relationship of the second skeleton points.

[0063] Specifically, the game SDK (Software Development Kit) receives the aforementioned parameters, adjusts the skeletal point position relationship of the virtual image according to the adjusted skeletal point position relationship diagram, and performs corresponding amplitude actions, that is, displays the virtual image according to the second skeletal point position relationship.

[0064] In an embodiment of the present application, the acquired adjustment parameters are used to adjust the positional relationship of the first skeletal points of the user's current actual action, thereby obtaining and displaying the positional relationship of the second skeletal points of the virtual image. The adjustment parameters include temperature information and information about the display device used to display the virtual image. Therefore, using the solution of an embodiment of the present application, a virtual image with different actions can be presented based on the user's actual action under different temperatures and / or different display device information, thereby improving the user experience.

[0065] Based on the above embodiment, the method may further include: receiving a video recording instruction from the user, and recording a game video according to the video recording instruction. The game video may be a video of the user playing the game, or a video of the game screen during the game. After the video is captured, the video may be processed, such as for sharing or editing.

[0066] Specifically, the "Record Video" and "End Recording" buttons can be displayed on the game display interface and displayed in a suspended form on the game interface. When the user clicks the button, the game system receives the user's video recording instruction accordingly. When the user clicks the end recording button, the background program actively saves the recorded game video to the cloud and generates the address where the game video is saved. The user can log in to his personal account on the cloud gaming platform client to view the recorded game video list, where the game may also include sharing, playback viewing and deletion functions. The system uploads the recorded video to the cloud resource server, generates a URL (Uniform Resource Locator), and adds it to the user's game video list.

[0067] Specifically, after the game video recording action is completed, the background program actively saves the recorded game video to the cloud and generates the address where the game video is saved. Users can log in to their accounts on the cloud gaming platform client to view the recorded game video list. In addition, it also includes the functions of sharing, viewing playback and deletion. If the user shares the video in the game video list, the user can click the share button and actively select the objects to share by group: such as the entire network, family, teammates, colleagues, etc. The object group label is actively set and added by the user. The shared user can receive a push message directly in the game video list and click the play button to open the game video for viewing. The background user behavior database will record the user's click and viewing behavior, including the number of clicks on the game video sharing message (the number of times the user views the same game video), the viewing time of the game video, and the type of game video.

[0068] On the basis of the above embodiment, the user group to which the user belongs may be determined, and corresponding video resources may be recommended to the user according to the user group.

[0069] Specifically, when determining user groups, the user's historical viewing history for various video types can be obtained, such as the number of clicks, video types viewed, total viewing time, and viewing time for each video. Subsequently, based on the user's historical viewing history for videos of the target type, a threshold for the user's attention to the target type of video is calculated. Video types may include adventure, leisure, action, sports, and competitive, among others. The target type is one of these types.

[0070] When the benchmark parameter is greater than or equal to the attention threshold, the user is divided into the user group corresponding to the target type video; wherein the benchmark parameter is the quotient of the number of clicks by the user on the target type video and the total number of clicks by the user on videos of various types.

[0071] Specifically, based on the user's historical viewing history, the user's proportion of videos of various types is calculated as a benchmark parameter. Videos may include adventure, leisure, action, sports, and competitive.

[0072] Specifically, the calculation method of the benchmark parameters is:

[0073] Among them, c a is the number of times a user views a certain type of game video, and s is the total number of clicks. For example, if a user has a total of 200 clicks, 120 of which are sports game videos and 40 of which are competitive game videos, then the user's percentage of sports game viewing, p, is 60%, and the percentage of competitive game videos, p, is 20%.

[0074] By calculating the value of p above, the p value obtained by the user for each type of video is compared with the threshold value corresponding to each type of video, thereby determining the group to which the user belongs. For example, the p value corresponding to the adventure video is compared with the threshold value (such as 60%). If p>60%, the user can be classified into the adventure group. Among them, the threshold values ​​corresponding to different types of videos may be the same or different. For some users who cannot be grouped, such as those who watch action game videos accounting for 30% (less than the threshold value corresponding to action game videos), those who watch sports game videos accounting for 31% (less than the threshold value for sports game videos), and those who watch adventure game videos accounting for 28% (less than the threshold value for adventure game videos), etc., in the embodiment of the present application, the following method can be used to determine the group to which they belong:

[0075] First, the user's historical viewing history for each video type is obtained. Next, based on the user's historical viewing history for the target video type, a threshold for the user's attention to the target video type is calculated. When a benchmark parameter is greater than or equal to the attention threshold, the user is assigned to the user group corresponding to the target video type. The benchmark parameter is the quotient of the number of clicks the user has made on the target video type divided by the total number of clicks the user has made on videos of all types. The attention threshold is the aforementioned p-value corresponding to the target video type.

[0076] For example, 1,000 users are selected. Among these 1,000 users, the proportion of some users who watch corresponding types of game videos is greater than the corresponding tag group threshold. For example, among the 1,000 users, the proportion of users belonging to the action group who watch action game videos is greater than 70%, and the proportion of users belonging to the sports group who watch sports game videos is greater than 75%. Such users can be directly divided into the action group, sports group, etc., and can be called extreme users. Among them, the tag group thresholds of different groups can be the same or different, and their tag group thresholds can be adjusted dynamically. However, as mentioned above, there may still be some users who cannot be grouped. Then, for such users, the attention threshold for the target type of video is calculated as follows.

[0077] For each type of game video a, the total number of user clicks S a , calculate the attention threshold T corresponding to the extreme user's video a a The attention threshold consists of two parts: average viewing time and replay rate. The specific calculation formula is as follows:

[0078]

[0079] Among them, c i is the number of views of user i, W i is the duration of the i-th viewing, t i , t i-1 They represent the time values ​​corresponding to the i-th moment and the i-1-th moment respectively.

[0080] For users who cannot be grouped, if the benchmark parameter p corresponding to the target type of video is greater than T a , then the user is classified into the group of videos of the target type, otherwise not into the group of the type. After completing the user grouping, based on the classification of games and game videos, games and game videos of related categories are recommended to users according to the group.

[0081] From the above description, it can be seen that in the embodiment of the present application, the influence of temperature on the user's muscle strength and the influence of the display terminal resolution on the user's gaming experience are taken into consideration. The player independently selects the gaming experience temperature, and the system automatically obtains the terminal display screen resolution, adds the influencing factor, and automatically adjusts the position relationship of the bone points, thereby improving the user experience. While having fun playing the game, the game players can truly experience the real impact of the temperature on the sport, just like playing skiing outdoors. They can also call up the video recording function with one click according to their needs. The system will also automatically recommend the user's favorite game videos based on the player's browsing behavior of other related videos. It can be seen that the solution of the embodiment of the present application enhances the fun, interactivity and sociality of ice and snow somatosensory game players.

[0082] The present application also provides an information processing device. Figure 5 , the information processing device 500 includes:

[0083] The first acquisition module 501 is used to obtain the first skeletal point position relationship of the user's actual action; the second acquisition module 502 is used to obtain the adjustment parameters; the first adjustment module 503 is used to obtain the second skeletal point position relationship of the user's virtual image based on the adjustment parameters and the first skeletal point position relationship; the first display module 504 is used to display the virtual image based on the second skeletal point position relationship; wherein the adjustment parameters are determined based on one or more of the following information: temperature information and information of the display device used to display the virtual image.

[0084] Optionally, the first acquisition module may include:

[0085] The first acquisition submodule is used to acquire continuous multiple-frame images of the actual action; the second acquisition submodule is used to determine the detection frame from the multiple-frame images according to a preset interval, and use the image between two consecutive detection frames as the tracking frame; the third acquisition submodule is used to acquire the skeleton point detection results in the detection frame and the skeleton point tracking results in the tracking frame; the fourth acquisition submodule is used to obtain the first skeleton point position relationship based on the skeleton point detection results and the skeleton point tracking results.

[0086] Optionally, the second acquisition module may include:

[0087] The first acquisition submodule is used to acquire the target action type of the actual action; the first determination submodule is used to determine the first adjustment parameter corresponding to the target action type according to the temperature information, and use the first adjustment parameter as the adjustment parameter.

[0088] Optionally, the first determining submodule is configured to:

[0089] When the target action type is an acceleration action or a jump action, calculating a difference between a temperature value of the temperature information corresponding to the actual action and a preset temperature threshold; calculating a first absolute value of a quotient of the difference and the preset temperature threshold; and using the absolute value of the difference between a reference value and the first absolute value as the first adjustment parameter;

[0090] When the target action type is a turning action, the difference between the temperature value of the temperature information corresponding to the actual action and the preset temperature threshold is calculated; the second absolute value of the quotient of the difference and the preset temperature threshold is calculated; and the absolute value of the sum of the reference value and the second absolute value is used as the first adjustment parameter.

[0091] The reference value may be 1.

[0092] Optionally, the second acquisition module may include:

[0093] The first acquisition submodule is used to acquire the target action type of the actual action; the first determination submodule is used to determine the second adjustment parameter corresponding to the target action type according to the resolution, and use the second adjustment parameter as the adjustment parameter.

[0094] The first determining submodule is configured to:

[0095] When the resolution is greater than a first preset value, the value of the second adjustment parameter is determined to be 1; when the resolution is less than or equal to the first preset value, the second adjustment parameter is the quotient of the product of the first coefficient and the second coefficient and the resolution; wherein the first coefficient and the second coefficient are greater than 0.

[0096] Optionally, the second acquisition module may include:

[0097] The first acquisition submodule is used to obtain the target action type of the actual action; the first determination submodule is used to determine the first adjustment parameter corresponding to the target action type based on the temperature information; the second determination submodule is used to determine the second adjustment parameter corresponding to the target action type based on the resolution; and the third acquisition submodule is used to use the first adjustment parameter and the second adjustment parameter to obtain the adjustment parameter corresponding to the target action type.

[0098] The first determining submodule is configured to:

[0099] When the target action type is an acceleration action or a jump action, calculating a difference between a temperature value of the temperature information corresponding to the actual action and a preset temperature threshold; calculating a first absolute value of a quotient of the difference and the preset temperature threshold; and using the absolute value of the difference between a reference value and the first absolute value as the first adjustment parameter;

[0100] When the target action type is a turning action, the difference between the temperature value of the temperature information corresponding to the actual action and the preset temperature threshold is calculated; the second absolute value of the quotient of the difference and the preset temperature threshold is calculated; and the absolute value of the sum of the reference value and the second absolute value is used as the first adjustment parameter.

[0101] The reference value may be 1.

[0102] The second determining submodule is configured to:

[0103] When the resolution is greater than a first preset value, the value of the second adjustment parameter is determined to be 1; when the resolution is less than or equal to the first preset value, the second adjustment parameter is the quotient of the product of the first coefficient and the second coefficient and the resolution; wherein the first coefficient and the second coefficient are greater than 0.

[0104] The third acquisition submodule is configured to use the product of the first adjustment parameter and the second adjustment parameter as the adjustment parameter corresponding to the target action type.

[0105] Optionally, the first adjustment module includes:

[0106] A first acquisition submodule, configured to acquire a first angle between a first target skeleton point and a second target skeleton point from the positional relationship of the first skeleton points;

[0107] a second acquisition submodule, configured to use the product of the first angle and the adjustment parameter as a second angle between the first target skeleton point and the second target skeleton point;

[0108] The first determining submodule is configured to form a second skeletal point position relationship of the virtual image using the second angle.

[0109] Optionally, the device may further include:

[0110] A first receiving module, configured to receive a video recording instruction from the user;

[0111] The first processing module is used to record the game video according to the video recording instruction.

[0112] Optionally, the device may further include:

[0113] A first determining module, configured to determine the user group to which the user belongs;

[0114] The second processing module is configured to recommend corresponding video resources to the user according to the user group.

[0115] The first determining module includes:

[0116] Obtain the user's historical viewing records of various types of videos;

[0117] A first acquisition submodule is configured to calculate a user's attention threshold for the target type of video based on the user's historical viewing records of the target type of video in the historical viewing records;

[0118] A first division submodule is configured to divide the user into a user group corresponding to the target type of video when the reference parameter is greater than or equal to the attention threshold;

[0119] The benchmark parameter is the quotient of the number of clicks by the user on the target type of video and the total number of clicks by the user on videos of various types.

[0120] The device provided in the embodiment of the present application can execute the above method embodiment, and its implementation principle and technical effects are similar, so this embodiment will not be repeated here.

[0121] It should be noted that the division of units in the embodiments of the present application is schematic and is merely a logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0122] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0123] An embodiment of the present application also provides an electronic device, comprising: a memory, a processor, and a program stored in the memory and executable on the processor; the processor is configured to read the program in the memory to implement the steps of the information processing method described above.

[0124] The embodiment of the present application also provides a readable storage medium, on which a program is stored. When the program is executed by the processor, the various processes of the above-mentioned information processing method embodiment are implemented, and the same technical effect is achieved. To avoid repetition, it is not repeated here. The readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disk, hard disk, tape, magneto-optical disk (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)), etc.

[0125] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0126] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD-ROM), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0127] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. An information processing method, characterized in that: include: Obtain the position relationship of the first skeleton point of the user's actual action; Get adjustment parameters; Obtaining a second skeleton point position relationship of the user's virtual image based on the adjustment parameter and the first skeleton point position relationship; displaying the virtual image according to the positional relationship of the second skeleton points; The adjustment parameter is determined based on one or more of the following information: Temperature information corresponding to the actual action and information of a display device for displaying the virtual image; Wherein, when the adjustment parameter includes a first adjustment parameter corresponding to the target action type of the actual action, or when the adjustment parameter is determined based on the first adjustment parameter corresponding to the target action type and the second adjustment parameter corresponding to the target action type, determining the first adjustment parameter includes: When the target action type is an acceleration action or a jump action, calculating a difference between a temperature value of the temperature information corresponding to the actual action and a preset temperature threshold; calculating a first absolute value of a quotient of the difference and the preset temperature threshold; and using the absolute value of the difference between a reference value and the first absolute value as the first adjustment parameter; When the target action type is a turning action, the difference between the temperature value of the temperature information corresponding to the actual action and the preset temperature threshold is calculated; the second absolute value of the quotient of the difference and the preset temperature threshold is calculated; and the absolute value of the sum of the reference value and the second absolute value is used as the first adjustment parameter.

2. The method according to claim 1, characterized in that The step of obtaining the position relationship of the first skeleton point of the actual action of the user includes: Acquiring a continuous multi-frame image of the actual action; Determining a detection frame from the multiple image frames according to a preset interval, and using an image between two consecutive detection frames as a tracking frame; Obtaining a skeleton point detection result in the detection frame and a skeleton point tracking result in the tracking frame; The positional relationship of the first skeleton points is obtained according to the skeleton point detection result and the skeleton point tracking result.

3. The method according to claim 1, characterized in that The obtaining of adjustment parameters includes: Get the target action type of the actual action; A first adjustment parameter corresponding to the target action type is determined according to the temperature information corresponding to the actual action, and the first adjustment parameter is used as the adjustment parameter.

4. The method according to claim 1, wherein The obtaining of adjustment parameters includes: Get the target action type of the actual action; A second adjustment parameter corresponding to the target action type is determined according to a resolution of a display device used to display the virtual image, and the second adjustment parameter is used as the adjustment parameter.

5. The method according to claim 1, wherein The obtaining of adjustment parameters includes: Get the target action type of the actual action; determining a first adjustment parameter corresponding to the target action type according to the temperature information corresponding to the actual action; determining a second adjustment parameter corresponding to the target action type according to a resolution of a display device used to display the virtual image; The first adjustment parameter and the second adjustment parameter are used to obtain an adjustment parameter corresponding to the target action type.

6. The method according to claim 4 or 5, characterized in that The determining, according to the resolution, a second adjustment parameter corresponding to the target action type includes: When the resolution is greater than a first preset value, the value of the second adjustment parameter is determined to be 1; When the resolution is less than or equal to the first preset value, the second adjustment parameter is a quotient of a product of a first coefficient and a second coefficient and the resolution; wherein the first coefficient and the second coefficient are greater than 0.

7. The method according to claim 5, characterized in that The obtaining of the adjustment parameter corresponding to the target action type by using the first adjustment parameter and the second adjustment parameter includes: The product of the first adjustment parameter and the second adjustment parameter is used as the adjustment parameter corresponding to the target action type.

8. The method according to claim 1, characterized in that The step of obtaining a second skeleton point position relationship of the user's virtual image based on the adjustment parameter and the first skeleton point position relationship includes: Acquire a first angle between a first target skeleton point and a second target skeleton point from the positional relationship of the first skeleton points; The product of the first angle and the adjustment parameter is used as the second angle between the first target skeleton point and the second target skeleton point; The second angle is used to form a second skeleton point position relationship of the virtual image.

9. An electronic device comprising: A memory, a processor, and a program stored in the memory and executable on the processor; wherein the processor is configured to read the program in the memory to implement the steps of the information processing method according to any one of claims 1 to 8.

10. A readable storage medium for storing a program, characterized in that: When the program is executed by a processor, the steps of the information processing method according to any one of claims 1 to 8 are implemented.

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