Bone posture data, bone posture determination method, device, medium and equipment

Abstract

The present disclosure provides bone posture data, a bone posture determination method, an apparatus, a medium, and a device, which relate to the animation technical field. The bone posture data determination method includes the steps of: identifying each preset pivotal part in a current motion of a target model (S101); extracting reference pivotal bone posture data for each preset pivotal part in the current motion from a pre-arranged motion spectrum to obtain target pivotal bone posture data for each preset pivotal part of the target model (S102), where the motion spectrum stores reference pivotal bone posture data for each preset pivotal part in different motions of a reference model; and determining intermediate bone posture data for bones other than the preset pivotal part bones of the target model based on the target pivotal bone posture data and the target model (S103). This solves the technical problem of time-consuming animation creation, thereby achieving the technical effects of reducing animation creation time and production costs.

Description

Cross-Citation of Related Applications

[0001] This disclosure claims priority to a Chinese patent application bearing application number 202211494288.3, ​​filed on November 25, 2022, and entitled "Bone Posture Data, Bone Posture Determination Method, Apparatus, Medium and Device," the entire contents of which are incorporated herein by reference. [Technical Field]

[0002] The present disclosure relates to the field of animation technology, and in particular to bone pose data, a bone pose determination method, an apparatus, a medium, and a device. [Background technology]

[0003] In game videos, bone animation is generally used to express character movements, i.e., a set of key frames is played back sequentially at a set frame rate to show the animation effect. The specific movements of the character are generally stored as key frame data, and each key frame data records the postures of all bones relative to their parent bones.

[0004] As the animation quality and movement complexity of characters in games improve, and the skeletons of different characters are different, animations are deeply bound to the skeletons of the characters, so currently it is necessary to create a large amount of animation for each character.

[0005] Therefore, creating animations now takes time.

[0006] It should be noted that the information disclosed in the above background art section is provided solely to enhance understanding of the background of the present disclosure and may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The present disclosure provides bone posture data, a bone posture determination method, a device, a medium, and an apparatus, and further reduces animation creation time.

[0008] According to a first aspect, an embodiment of the present disclosure provides a bone posture data determination method, the bone posture data determination method including: identifying each predetermined vital point in the current operation of the model being processed; A step of extracting reference pivotal bone posture data of each preset pivotal part in a current motion from a pre-arranged motion spectrum, and obtaining target pivotal bone posture data of each preset pivotal part of a processing target model, wherein the motion spectrum stores reference pivotal bone posture data of each preset pivotal part in different motions of the reference model; and determining intermediate bone posture data of bones other than the predetermined pivotal bones in the model to be processed based on the target pivotal bone posture data and the model to be processed.

[0009] In one alternative embodiment of the present disclosure, before extracting reference pivotal bone posture data of each preset pivotal part in the current motion from the preset motion spectrum, and obtaining target pivotal bone posture data of each preset pivotal part of the processing target model, the bone posture data determination method includes: Obtaining motion postures for different motions of a reference model; extracting reference pivotal bone posture data of each preset pivotal part in the posture of the movement for each movement; The method further includes generating a motion spectrum based on each reference pivotal bone posture data corresponding to each motion.

[0010] In one alternative embodiment of the present disclosure, the step of extracting reference pivotal bone posture data of each preset pivotal part in the current motion from the preset motion spectrum, and obtaining target pivotal bone posture data of each preset pivotal part of the processing target model includes: Extracting reference pivotal bone posture data of each preset pivotal part in the current motion from the pre-arranged motion spectrum, and obtaining initial pivotal bone posture data of each preset pivotal part of the processing target model; determining a body shape scaling ratio of the processing target model relative to the reference model based on reference body shape data of the reference model and current body shape data of the processing target model; and proportionally correcting the initial pivotal bone posture data based on the body shape scaling ratio to obtain target pivotal bone posture data for each preset pivotal part of the processing target model.

[0011] In one optional embodiment of the present disclosure, before determining a body shape scaling ratio of the processing target model to the reference model based on reference body shape data of the reference model and current body shape data of the processing target model, the bone posture data determination method includes: determining body type parameters of a reference model in a preset reference posture to obtain reference body type data; The method further includes a step of determining body type parameters of the processing target model in a preset reference posture and acquiring current body type data.

[0012] In one alternative embodiment of the present disclosure, the step of determining intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model includes: determining terminal position information of each predetermined vital part of the model to be processed; and solving bone postures of bones other than the predetermined pivotal bones in the processing target model using an inverse kinematics algorithm based on the end position information and the target pivotal bone posture data, thereby obtaining intermediate bone posture data.

[0013] In one alternative embodiment of the present disclosure, the step of determining intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model includes: The method includes a step of inputting target pivotal bone posture data into a bone posture determination model and obtaining intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed, and the bone posture determination model is trained based on the bone posture data in different movements of the model to be processed.

[0014] In one alternative embodiment of the present disclosure, the motion spectrum further includes a motion paraphrase for each motion, and the motion paraphrase is set to indicate the motion content of the current motion, and the bone posture data determination method includes: extracting a target motion paraphrase corresponding to the current motion from the motion spectrum; The method further includes a step of correcting the desired key bone posture data and the intermediate bone posture data based on the desired motion paraphrase to obtain the desired bone posture data of the processing target model.

[0015] In one alternative embodiment of the present disclosure, when the current motion is a contact fit between a first portion of the processing target model and a target object, the step of correcting the target pivotal bone posture data and the intermediate bone posture data based on the target motion paraphrase to obtain the target bone posture data of the processing target model includes: determining a target position of a target object; correcting the terminal bone posture of the first part to a target position and acquiring the current bone posture of the processing target model; Extracting bone posture data of the current bone posture to obtain target bone posture data.

[0016] In one selectable embodiment of the present disclosure, the step of correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the processing target model includes: a step of performing a collision test between the first part and the target object based on the bone posture data of the first part and the target position, and obtaining a collision contact compatible position between the first part and the target object; and correcting the end bone posture of the first part to a position corresponding to the collision contact compatible position, and obtaining the current bone posture of the processing target model.

[0017] In one alternative embodiment of the present disclosure, the target object is a second part of the model to be processed, and the operation spectrum further includes a second part marker of the second part; Correspondingly, the step of correcting the terminal bone posture of the first part to the target position and acquiring the current bone posture of the processing target model includes: The method includes a step of correcting the terminal bone posture of the first part to a position corresponding to the second part marker, and acquiring the current bone posture of the model to be processed.

[0018] In one alternative embodiment of the present disclosure, the pre-defined vital parts include at least one of the head, limbs, buttocks, and shoulders.

[0019] According to a second aspect, an embodiment of the present disclosure provides a bone pose determination method, the bone pose determination method including: a step of acquiring reference pivotal bone posture data and intermediate bone posture data of a processing target model, the reference pivotal bone posture data and the intermediate bone posture data being determined based on the bone posture data determination method described in any one of the above; and generating a bone posture of a processing target model based on the reference pivotal bone posture data and the intermediate bone posture data.

[0020] According to a third aspect, an embodiment of the present disclosure provides a bone pose data determination device, the bone pose data determination device comprising: an identification module, an extraction module, and a determination module; the identification module is configured to identify each predetermined vital point in the current operation of the processed model; The extraction module is configured to extract reference pivotal bone posture data of each preset pivotal part in a current motion from the pre-arranged motion spectrum, and obtain target pivotal bone posture data of each preset pivotal part of the processing target model, wherein the motion spectrum stores the reference pivotal bone posture data of each preset pivotal part in different motions of the reference model; The determination module is configured to determine intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model.

[0021] According to a fourth aspect, an embodiment of the present disclosure provides a bone attitude determination device, the bone attitude determination device comprising: an acquisition module; and a generation module; the acquisition module is configured to acquire reference pivotal bone posture data and intermediate bone posture data of the processing target model, the reference pivotal bone posture data and the intermediate bone posture data being determined based on the bone posture data determination method according to any one of the above claims; The generation module is configured to generate a bone posture of the processing target model based on the reference pivotal bone posture data and the intermediate bone posture data.

[0022] According to a fifth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, the computer program implementing the above method when executed by a processor.

[0023] According to a sixth aspect, an embodiment of the present disclosure provides an electronic device including a processor and a memory configured to store executable instructions for the processor, the processor configured to perform the above method by executing the executable instructions.

[0024] The technical solution of the present disclosure has the following beneficial effects:

[0025] The above bone posture data determination method preliminarily arranges pivotal bone posture data of preset pivotal parts including different movements based on a reference model, and when determining bone posture data for any type of target model, first identifies each preset pivotal part in the current movement of the target model, then extracts target pivotal bone posture data of each preset pivotal part in the current movement from the movement spectrum, and then simply determines intermediate bone posture data of bones other than the preset pivotal part bones in the target model based on the target pivotal bone posture data, thereby obtaining bone data for all bones in the target model. According to the first aspect, the reference model enables different movements to be mapped to different target models, thereby avoiding the need to redevelop the same movement multiple times in different models, and greatly reducing the amount of work required for animation development, thereby solving the current technical problem of time-consuming animation creation and achieving the technical effects of reducing animation creation time and creation costs. According to the second aspect, the embodiments of the present disclosure store key bone posture data of preset key parts of the reference model based on the movement spectrum, thereby greatly saving storage space compared to the conventional situation of storing all key bone posture data for different movement frames of different models.

[0026] It should be noted that the above general and detailed descriptions are merely illustrative and are not intended to limit the present disclosure. [Brief explanation of the drawings]

[0027] The drawings herein are incorporated into the specification and constitute a part of this specification, are adapted to the embodiments of the present disclosure, and are used together with the specification to interpret the principles of the present disclosure. It is apparent that the drawings in the following description are merely some embodiments of the present disclosure, and those skilled in the art can obtain other drawings based on these drawings without any creative effort. [Figure 1]10 is a flowchart illustrating a method for determining bone posture data in the exemplary embodiment. [Figure 2] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 3] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 4] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 5] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 6] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 7] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 8] 1 shows a flowchart of a method for determining bone pose data in the present exemplary embodiment; [Figure 9] 10 is a flowchart illustrating a bone pose determination method according to the present exemplary embodiment. [Figure 10] FIG. 2 is a schematic diagram illustrating the structure of a bone posture data determination device according to the present exemplary embodiment; [Figure 11] 1 is a schematic diagram illustrating the structure of a bone attitude determination device in this exemplary embodiment; [Figure 12] 1 is a schematic diagram illustrating a structure of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0028] Next, exemplary embodiments will be described in more detail with reference to the drawings. However, the exemplary embodiments may be embodied in various forms and should not be understood as being limited to the examples described herein. On the contrary, these embodiments are provided to make the present disclosure more comprehensive and complete and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be incorporated in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of the embodiments of the present disclosure. However, those skilled in the art will recognize that the technical aspects of the present disclosure can be implemented without one or more of the specific details, or that other methods, components, devices, steps, etc. can be employed. In other cases, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0029] Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings indicate the same or similar parts, and redundant description will be omitted. Some of the block diagrams shown in the drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor and / or microcontroller devices.

[0030] The flowcharts shown in the drawings are merely exemplary and do not necessarily include all steps, for example, some steps may be separated, some steps may be integrated or partially integrated, and the order in which the steps are actually performed may vary depending on the actual situation.

[0031] In the prior art, game videos generally use bone animation to express character movements, i.e., a set of key frames is sequentially played at a set frame rate to show animation effects. A character's specific movements are generally stored as key frame data, and each key frame data records the posture of all bones relative to their parent bones. With the improvement in the animation quality and movement complexity of game characters, and the fact that different characters have different skeletal structures, animations are deeply bound to the character's skeletal structure, currently requiring the creation of a large amount of animation for each character. Therefore, the current animation creation process is time-consuming.

[0032] In view of the above problems, an embodiment of the present disclosure provides a bone posture data determination method, further shortening the time required to create animation. The bone posture data determination method according to the embodiment of the present disclosure is applied to a terminal device, and the terminal device applies the display method according to the embodiment of the present disclosure to the terminal device. The terminal device may be a service terminal, a user terminal, or the like. The following description will be given taking the terminal device as the execution entity and applying the bone posture data determination method to the terminal device to determine bone data of a model to be processed as an example. Referring to FIG. 1, the bone posture data determination method according to the embodiment of the present disclosure includes the following steps 101 to 103.

[0033] In step 101, each pre-defined critical point in the current operation of the model being processed is identified.

[0034] The target model refers to a three-dimensional model of a virtual character, such as a monster, warrior, or human. The virtual character corresponding to the target model is a mobile, non-static object that can exhibit different poses or perform different movements. The movement of the target model is the movement of the virtual character corresponding to the target model represented by the model's pose. Animation is formed by continuously playing back independent movement frames. Each movement frame contains at least one movement composed of the target model. When one movement is formed, other different parts have coordinate values ​​corresponding to different positions, such as the head, limbs, waist, buttocks, and tail. The preset key parts are reference parts, such as the head and limbs, preset to represent the model's movement, and the current movement is represented by the head and limbs. The predetermined key parts may be specifically set according to actual circumstances. For example, for a reptile, the predetermined key parts may be the head, limbs, back, and tail; for a human, the predetermined key parts may be the head and limbs. Of course, this is merely an example, and the embodiments of the present disclosure are not specifically limited.

[0035] In step 102, the reference pivotal bone posture data of each preset pivotal part in the current motion is extracted from the pre-arranged motion spectrum, and the target pivotal bone posture data of each preset pivotal part of the model to be processed is obtained.

[0036] The target model includes at least one skeleton consisting of different bones. Of course, other components, such as muscles and skin, may also be included; the embodiments of the present disclosure are not specifically limited. Bones refer to different part nodes. For example, the bones included in a hand include the index finger bone, middle finger bone, and thumb bone. A single movement corresponds to a series of movement postures. When the target model is in the movement posture, each part corresponds to a different position, and the bones in the part correspond to different bone posture data. The bone posture data may include bone coordinates and orientations as parameters representing the state of the bone in the current movement frame. The movement spectrum stores reference key bone posture data for each preset key part of the reference model in different movements. The terminal device can obtain target key bone posture data corresponding to the current movement simply by searching the movement spectrum based on the movement markers of the current movement.

[0037] In step 103, intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed is determined based on the target pivotal bone posture data and the model to be processed.

[0038] After obtaining the target pivotal bone posture data of the predetermined pivotal parts, the intermediate bone posture data can be obtained in several ways. The first way is to use the pivotal bone as a parent bone, one of which is a child bone, and determine the corresponding child bone according to the mapping or traction relationship between the parent bone and the child bone, and determine the posture data of the child bone to obtain the intermediate bone posture data. The second way is to use a pre-trained neural network model to predict and calculate the intermediate bone posture data using the obtained target pivotal bone posture data as input. The third way is to back-calculate the model to be processed using the target pivotal bone posture data to obtain the intermediate bone posture data. The ways of determining the intermediate bone posture data include, but are not limited to, the above three ways, and are not comprehensive here.

[0039] The bone posture data determination method provided by the embodiments of the present disclosure pre-arranges pivotal bone posture data of preset pivotal parts including different movements based on a reference model. When determining bone posture data for any type of target model, first identify each preset pivotal part in the current movement of the target model, then extract target pivotal bone posture data of each preset pivotal part in the current movement from the movement spectrum, and then determine intermediate bone posture data of other bones in the target model other than the preset pivotal part bones based on the target pivotal bone posture data, thereby obtaining bone data for all bones in the target model. According to the first aspect, the reference model enables different movements to be mapped to different target models, thereby avoiding the need to redevelop the same movement multiple times in different models, and greatly reducing the amount of work required for animation development, thereby solving the current technical problem of time-consuming animation creation and achieving the technical effects of reducing animation creation time and creation costs. According to the second aspect, the embodiments of the present disclosure store key bone posture data of preset key parts of the reference model based on the movement spectrum, thereby greatly saving storage space compared to the conventional situation of storing all key bone posture data for different movement frames of different models.

[0040] Referring to FIG. 2, in one optional embodiment of the present disclosure, before extracting the reference pivotal bone posture data of each preset pivotal part in the current motion from the preset motion spectrum in the above step 102 and obtaining the target pivotal bone posture data of each preset pivotal part of the model to be processed, the bone posture data determination method further includes the following steps 201 to 203.

[0041] In step 201, the motion postures of the reference model in different motions are obtained.

[0042] The reference model always corresponds to one posture when expressing one action, such as a posture with hands on hips, a handstand, etc. The action and the corresponding posture are already placed when the developer designs the animation, and can be obtained simply by extracting them from the pre-placed source file.

[0043] In step 202, for each movement, reference pivotal bone posture data of each preset pivotal part in the movement posture is extracted.

[0044] The developer represents different pre-designed movements using a reference model, records the movement posture in the movement frame for each movement, and then extracts bone posture data of the pre-set key parts from the movement posture, such as the bone position and orientation of the head, and the bone positions and orientations of the limbs.

[0045] In step 203, a motion spectrum is generated based on the posture data of each reference pivotal bone corresponding to each motion.

[0046] For each motion posture, the bone posture data extracted in step 202 above can be stored in the corresponding motion in a motion spectrum to obtain the motion spectrum, where the motion spectrum includes the bone posture data of each pre-defined pivotal part in different motion states of the reference model.

[0047] The embodiment of the present disclosure first obtains the movement postures of the reference model in different movements, then extracts the reference pivotal bone posture data of each pre-defined pivotal part in the movement posture for each movement, and finally obtains a movement spectrum including the reference pivotal bone posture data corresponding to each movement, which greatly reduces the amount of data that needs to be stored for bone posture data of all bones in each movement when performing movement mapping in the prior art solutions, and saves storage space.

[0048] Referring to FIG. 3, in one optional embodiment of the present disclosure, in the above step 102, the step of extracting the reference pivotal bone posture data of each preset pivotal part in the current motion from the preset motion spectrum and obtaining the target pivotal bone posture data of each preset pivotal part of the model to be processed includes the following steps 301 to 303.

[0049] In step 301, the reference pivotal bone posture data of each preset pivotal part in the current motion is extracted from the pre-arranged motion spectrum, and the initial pivotal bone posture data of each preset pivotal part of the processing target model is obtained.

[0050] Based on the same method as in step 102 above, the terminal device can obtain key bone posture data corresponding to the current motion by searching the motion spectrum based on the motion marker of the current motion, and set the key bone posture data as the initial key bone posture data.

[0051] In step 302, a body shape scaling ratio of the processing target model to the reference model is determined based on the reference body shape data of the reference model and the current body shape data of the processing target model.

[0052] The reference model is a model used when generating the motion spectrum, and the target model is a model actually required when performing animation design or motion mapping, and the two models have different body shape data, which may include, but are not limited to, height, limb length, hand length, foot length and width, etc. The body shape scaling ratio may be the ratio between the reference body shape data and the current body shape data.

[0053] In step 303, the initial pivotal bone posture data is proportionally corrected based on the body shape scaling ratio to obtain the target pivotal bone posture data of each preset pivotal part of the processing target model.

[0054] Proportional correction refers to obtaining target pivotal bone posture data of each preset pivotal part of the processing target model by enlarging or reducing the obtained initial pivotal bone posture data according to a body shape scaling ratio.

[0055] In the embodiment of the present disclosure, initial pivotal bone posture data of each preset pivotal part in the current movement is extracted from the pre-arranged movement spectrum, and then a body shape scaling ratio of the target model to the reference model is determined based on the reference body shape data of the reference model and the current body shape data of the target model. Finally, a proportional correction is made to the initial pivotal bone posture data based on the body shape scaling ratio to obtain target pivotal bone posture data that is more suitable for the target model, and the mapping effect of mapping the movement of the reference model to the target model is better, and the movement expression effect of the obtained target model is better.

[0056] Referring to FIG. 4, in one optional embodiment of the present disclosure, before determining the body shape scaling ratio of the target model to the reference model based on the reference body shape data of the reference model and the current body shape data of the target model in the above step 302, the bone posture data determination method further includes the following steps 401 to 402.

[0057] In step 401, the body type parameters of the reference model in a preset reference posture are determined to obtain reference body type data.

[0058] In step 402, the body type parameters of the processing target model in a preset reference posture are determined, and current body type data is obtained.

[0059] Here, the preset reference posture is a posture preset for measuring the reference model and the model to be processed, such as the TPoe posture (a posture in which the limbs are spread apart). By determining the current body shape data of the model to be processed using the same preset reference posture as the reference model, the body shape scaling ratio determined based on the current body shape data and the reference body shape data is more accurate, and the reliability of the target cardinal bone posture data obtained after proportionally correcting the initial cardinal bone posture data based on the body shape scaling ratio can be further improved, thereby further improving the suitability of the motion mapping and the effect of motion expression.

[0060] In one optional embodiment of the present disclosure, in the above step 103, determining intermediate bone posture data of bones other than the preset pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model is not limited to the following two types:

[0061] In the first method, intermediate bone posture data is determined using an IK (Inverse Kinematics) algorithm, and specifically, referring to FIG. 5, the method includes the following steps 501 to 502.

[0062] In step 501, the terminal position information of each preset vital part of the model to be processed is determined.

[0063] For example, the preset vital parts are the limbs, the extremity positions are the fingers and toes, and the corresponding extremity position information is the coordinate positions of the fingers and toes in the current motion frame.

[0064] In step 502, based on the end position information and the target pivotal bone posture data, the bone postures of the bones other than the preset pivotal bones in the processing target model are solved by an inverse kinematics algorithm to obtain intermediate bone posture data.

[0065] The embodiments of the present disclosure determine the intermediate bone posture data of the model to be processed based on an inverse kinematics algorithm, and such a method has a fast solution speed and can greatly improve the efficiency of determining bone posture data according to the embodiments of the present disclosure.

[0066] In the second method, the step of determining intermediate bone posture data using a neural network model specifically includes the following steps:

[0067] The target pivotal bone posture data is input to the bone posture determination model, and intermediate bone posture data of bones other than the pivotal bones preset in the processing target model is obtained.

[0068] Here, the bone posture determination model is trained based on bone posture data of different movements of the target model. The training sample is each bone posture data in the skeleton of the target model. In actual application, other intermediate bone posture data can be obtained by using some target key bone posture data. Each target model has a set of matching neural network models, so that the obtained intermediate bone posture data is more accurate and can present different movement effects for different target models, and can more accurately represent the movement characteristics of the target model, resulting in better movement expression effects.

[0069] In one alternative embodiment of the present disclosure, the motion spectrum further includes a motion paraphrase for each motion, where the motion paraphrase is set to indicate the motion content of the current motion. Note that, since a motion or a motion posture is generally present as bone posture data, i.e., coordinate position information, in a motion frame, in order to more clearly express the current motion, in an embodiment of the present disclosure, a corresponding motion paraphrase, such as "put your right hand on your hip" or "touch your left foot on the ground," is set in the motion spectrum for each motion or some important motions, so as to more clearly express the current motion. Referring to FIG. 6, the bone posture data determination method further includes the following steps 601 to 602.

[0070] In step 601, a target action paraphrase corresponding to the current action is extracted from the action spectrum.

[0071] The terminal device can search for an action paraphrase corresponding to the current action from the action spectrum based on the action marker of the current action and interpret it as a target action paraphrase.

[0072] In step 602, the target key bone posture data and the intermediate bone posture data are posture-corrected based on the target motion paraphrase to obtain the target bone posture data of the processing target model.

[0073] In the embodiments of the present disclosure, by setting a motion paraphrase for each motion in the motion spectrum, when performing motion mapping, the bone posture data in the target model can be corrected based on the target motion paraphrase of the obtained current motion, thereby realizing the occurrence of a situation in which defects or even errors appear in partial motions, improving the reliability of the obtained target bone posture data, and further improving the expressive effect of the current motion in the target model.

[0074] In one alternative embodiment of the present disclosure, the current action is a contact fit between a first part of the processing target model and a target object, for example, "contact the left foot with the ground", where the first part is the left foot and the target object is the ground. Correspondingly, referring to Figure 7, in the above step 602, the step of correcting the target key bone posture data and the intermediate bone posture data based on the target action paraphrase to obtain the target bone posture data of the processing target model includes the following steps 701 to 703.

[0075] In step 701, a target position of the target object is determined.

[0076] In a game scene, the position of each object is fixed in one frame of the screen, and the coordinates of the location of the target object can be directly determined for the corresponding action frame or image frame. The target object can be any object in the game scene, including a certain part of the model to be processed, and is not particularly limited here, and can be specifically selected or set according to the actual situation.

[0077] In step 702, the terminal bone posture of the first part is corrected to the target position, and the current bone posture of the processing target model is obtained.

[0078] The terminal bone is the last bone in the direction in which the first part extends outward from a position close to the center point of the model to be processed. The posture shown by the model to be processed after the first part and the target object are contact-fitted is the current model posture, and the posture corresponding to each bone in the current model posture is the current bone posture.

[0079] In step 703, bone posture data of the current bone posture is extracted to obtain target bone posture data.

[0080] That is, by determining the coordinate positions and directional positions corresponding to each current bone, it is possible to obtain target pivotal bone posture data and intermediate bone posture data for the model to be processed, and the target pivotal bone posture data and intermediate bone posture data constitute the target bone posture data for the model to be processed.

[0081] The embodiments of the present disclosure determine the target position of the target object, correct the terminal bone posture of the first part to the target position, obtain the current bone posture of the model to be processed, and then extract the target bone posture data from the current bone posture, thereby avoiding situations such as over-correction when directly adjusting the bone posture and further improving the reliability of the target bone posture data.

[0082] Referring to FIG. 8, in one optional embodiment of the present disclosure, in the above step 702, the step of correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the model to be processed includes the following steps 801 to 802.

[0083] In step 801, a collision test is performed between the first part and the target object based on the bone posture data of the first part and the target position, and a collision contact compatible position between the first part and the target object is obtained.

[0084] The collision contact matching position is a contact matching position between the first portion and the target object, such as a contact matching surface or a contact matching point.

[0085] In step 802, the end bone posture of the first part is corrected to a position corresponding to the collision contact matching position, and the current bone posture of the processing target model is obtained.

[0086] In the embodiment of the present disclosure, a collision test is first performed between the first part and the target object, and then the terminal bone posture of the first part is corrected to a position corresponding to the collision contact compatible position. This prevents the occurrence of situations where the feet are pressed into the ground or the hands are inserted into the body even though the bones do not overlap due to the thickness of the first part being too large or the thickness of the target object being too large, and improves the effect of motion expression. In one optional embodiment of the present disclosure, the target object is a second part of the model to be processed, and the motion spectrum further includes a second part marker of the second part, for example, a waist marker of the waist, and the second part marker may be in any form, for example, a marker point or a character marker or any other form of marker, and is not specifically limited herein.

[0087] Correspondingly, in step 702, the step of correcting the terminal bone posture of the first part to the target position and acquiring the current bone posture of the processing target model is The method includes a step of correcting the terminal bone posture of the first part to a position corresponding to the second part marker, and acquiring the current bone posture of the model to be processed.

[0088] For example, if the current action is "putting the right hand on the waist", i.e., the right hand is the first part and the waist is the second part, then the end bone posture of the hand, i.e., the bone posture of the fingers, can be adjusted to the position of the waist based on the second part marker of the waist, and the current bone posture of the model to be processed is the above current bone posture.

[0089] In one alternative embodiment of the present disclosure, the preset pivotal parts include at least one of the head, limbs, buttocks, and shoulders, and each motion posture of the reference model is determined by the bones of these pivotal parts, making the motion posture relatively accurate and versatile.

[0090] Referring to FIG. 9, an embodiment of the present disclosure provides a bone posture determination method, which includes the following steps 901 to 902.

[0091] In step 901, the reference pivotal bone posture data and intermediate bone posture data of the processing target model are obtained.

[0092] Here, the reference key bone posture data and intermediate bone posture data are determined based on one of the above bone posture data determination methods, and the beneficial effects of the bone posture data determination method have already been explained in detail in the above embodiments, so further explanation will be omitted here.

[0093] In step 902, a bone posture of the processing target model is generated based on the reference pivotal bone posture data and the intermediate bone posture data.

[0094] The embodiments of the present disclosure determine and acquire reference pivotal bone posture data and intermediate bone posture data of the model to be processed based on the above bone posture data determination method, and then directly generate the bone posture of the model to be processed based on the reference pivotal bone posture data and intermediate bone posture data, which is more efficient than conventional posture generation that requires bone posture data for each bone to be constructed individually.

[0095] 10, to realize the bone posture data determination method, an embodiment of the present disclosure provides a bone posture data determination apparatus 1000. Figure 10 is a schematic configuration diagram of the bone posture data determination apparatus 1000. Here, the bone posture data determination apparatus 1000 includes an identification module 1010, an extraction module 1020, and a determination module 1030.

[0096] The identification module 1010 is configured to identify each pre-defined critical point in the current operation of the model to be processed.

[0097] The extraction module 1020 is configured to extract reference pivotal bone posture data of each preset pivotal part in a current motion from a pre-arranged motion spectrum, and obtain target pivotal bone posture data of each preset pivotal part of the processing target model, where the motion spectrum stores the reference pivotal bone posture data of each preset pivotal part in different motions of the reference model.

[0098] The determination module 1030 is configured to determine intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model.

[0099] In one alternative embodiment, the extraction module 1020 is further configured to obtain motion postures of the reference model in different motions, extract reference pivotal bone posture data of each pre-defined pivotal part in the motion posture for each motion, and generate a motion spectrum based on each reference pivotal bone posture data corresponding to each motion.

[0100] In one alternative embodiment, the extraction module 1020 is specifically configured to extract reference pivotal bone posture data of each preset pivotal part in the current motion from the pre-arranged motion spectrum, obtain initial pivotal bone posture data of each preset pivotal part of the model to be processed, determine a body shape scaling ratio of the model to be processed relative to the reference model according to the reference body shape data of the reference model and the current body shape data of the model to be processed, proportionally correct the initial pivotal bone posture data according to the body shape scaling ratio, and obtain target pivotal bone posture data of each preset pivotal part of the model to be processed.

[0101] In one alternative embodiment, the extraction module 1020 is specifically configured to determine body shape parameters of a reference model in a preset reference posture, obtain reference body shape data, determine body shape parameters of a target model in a preset reference posture, and obtain current body shape data.

[0102] In one alternative embodiment, the determination module 1030 is specifically configured to determine end position information of each preset pivotal part of the processing target model, and solve the bone postures of other bones in the processing target model other than the preset pivotal part bones by an inverse kinematics algorithm based on the end position information and the target pivotal bone posture data, to obtain intermediate bone posture data.

[0103] In one alternative embodiment, the determination module 1030 is specifically configured to input target pivotal bone posture data into a bone posture determination model, and obtain intermediate bone posture data of other bones other than the preset pivotal bones in the target model, and the bone posture determination model is trained based on the bone posture data of the target model in different movements.

[0104] In one alternative embodiment, the motion spectrum further includes a motion paraphrase for each motion, and the motion paraphrase is set to indicate the motion content of the current motion. The extraction module 1020 is further configured to extract a target motion paraphrase corresponding to the current motion from the motion spectrum, and perform posture correction on the target key bone posture data and intermediate bone posture data based on the target motion paraphrase to obtain target bone posture data of the model to be processed.

[0105] In one alternative embodiment, when the current operation is a contact fit between a first part in the processing target model and a target object, the determination module 1030 is specifically configured to determine a target position of the target object, correct the end bone posture of the first part to the target position, obtain the current bone posture of the processing target model, extract bone posture data of the current bone posture, and obtain the target bone posture data.

[0106] In one alternative embodiment, the determination module 1030 is specifically configured to perform a collision test between the first part and the target object based on the bone posture data of the first part and the target position, obtain a collision contact matching position between the first part and the target object, correct the end bone posture of the first part to a position corresponding to the collision contact matching position, and obtain the current bone posture of the model to be processed.

[0107] In one alternative embodiment, the target object is a second part of the model to be processed, and the motion spectrum further includes a second part marker of the second part, and the determination module 1030 is specifically configured to correct the end bone posture of the first part to a position corresponding to the second part marker, and obtain the current bone posture of the model to be processed.

[0108] In one alternative embodiment, the pre-defined vital parts include at least one of the head, limbs, buttocks, and shoulders.

[0109] Referring to FIG. 11, to realize the above bone posture determination method, an embodiment of the present disclosure provides a bone posture determination device 1100, which includes an acquisition module 1110 and a generation module 1120.

[0110] The acquisition module 1110 is configured to acquire reference pivotal bone posture data and intermediate bone posture data of the model to be processed, and the reference pivotal bone posture data and intermediate bone posture data are determined based on any one of the bone posture data determination methods described above.

[0111] The generation module 1120 is configured to generate a bone posture of the processing target model based on the reference pivotal bone posture data and the intermediate bone posture data.

[0112] Exemplary embodiments of the present disclosure further provide a computer-readable storage medium, which may be implemented in the form of a program product containing program code. When the program product runs on an electronic device, the program code is used to cause the electronic device to perform steps according to various exemplary embodiments of the present disclosure described in the "exemplary method" section herein. In one embodiment, the program product is embodied as a portable compact disc read-only memory (CD-ROM), contains the program code, and can run on a terminal device such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this file, the readable storage medium may be any tangible medium that contains or stores a program that can direct the execution of, or be used in conjunction with, a system, apparatus, or device.

[0113] In an exemplary embodiment of the present disclosure, a computer-readable signal medium is provided, which identifies each preset pivotal part in a current motion of a model to be processed, extracts reference pivotal bone posture data of each preset pivotal part in the current motion from a pre-arranged motion spectrum, obtains target pivotal bone posture data of each preset pivotal part of the model to be processed, the motion spectrum stores the reference pivotal bone posture data of each preset pivotal part in different motions of the reference model, and determines intermediate bone posture data of other bones in the model to be processed other than the preset pivotal part bones according to the target pivotal bone posture data and the model to be processed.

[0114] In an exemplary embodiment of the present disclosure, based on the above solution, before extracting reference pivotal bone posture data of each preset pivotal part in a current movement from a pre-arranged movement spectrum and obtaining target pivotal bone posture data of each preset pivotal part of a model to be processed, the bone posture data determination method further includes the steps of obtaining movement postures of the reference model in different movements, extracting reference pivotal bone posture data of each preset pivotal part in a movement posture for each movement, and generating a movement spectrum based on each reference pivotal bone posture data corresponding to each movement.

[0115] In an exemplary embodiment of the present disclosure, based on the above solution, the step of extracting reference pivotal bone posture data of each preset pivotal part in the current movement from the pre-arranged motion spectrum and obtaining target pivotal bone posture data of each preset pivotal part of the model to be processed includes the steps of: extracting reference pivotal bone posture data of each preset pivotal part in the current movement from the pre-arranged motion spectrum and obtaining initial pivotal bone posture data of each preset pivotal part of the model to be processed; determining a body shape scaling ratio of the model to be processed relative to the reference model based on the reference body shape data of the reference model and the current body shape data of the model to be processed; and proportionally correcting the initial pivotal bone posture data based on the body shape scaling ratio to obtain target pivotal bone posture data of each preset pivotal part of the model to be processed.

[0116] In an exemplary embodiment of the present disclosure, based on the above solution, before determining the body shape scaling ratio of the target model to the reference model based on the reference body shape data of the reference model and the current body shape data of the target model, the bone posture data determination method further includes a step of determining body shape parameters in a preset reference posture of the reference model and obtaining reference body shape data, and a step of determining body shape parameters in a preset reference posture of the target model and obtaining current body shape data.

[0117] In an exemplary embodiment of the present disclosure, based on the above solution, the step of determining intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed based on the target pivotal bone posture data and the model to be processed includes: determining end position information of each preset pivotal part of the model to be processed; and solving the bone postures of bones other than the preset pivotal bones in the model to be processed by an inverse kinematics algorithm based on the end position information and the target pivotal bone posture data, to obtain intermediate bone posture data.

[0118] In an exemplary embodiment of the present disclosure, based on the above solution, the step of determining intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed based on the target pivotal bone posture data and the model to be processed includes the steps of inputting the target pivotal bone posture data into a bone posture determination model to obtain intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed, and the bone posture determination model is trained based on the bone posture data of the model to be processed in different movements.

[0119] In an exemplary embodiment of the present disclosure, based on the above solution, the motion spectrum further includes a motion paraphrase for each motion, and the motion paraphrase is set to indicate the motion content of the current motion. The bone posture data determination method further includes: extracting a target motion paraphrase corresponding to the current motion from the motion spectrum; and posture correcting the target key bone posture data and intermediate bone posture data based on the target motion paraphrase to obtain target bone posture data of the model to be processed.

[0120] In an exemplary embodiment of the present disclosure, based on the above solution, when the current motion is a contact fit between a first part of the model to be processed and a target object, the step of posture correcting the target pivotal bone posture data and the intermediate bone posture data based on the target motion paraphrase and obtaining the target bone posture data of the model to be processed includes the steps of determining a target position of the target object, correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the model to be processed, and extracting the bone posture data of the current bone posture and obtaining the target bone posture data.

[0121] In an exemplary embodiment of the present disclosure, based on the above solution, the step of correcting the end bone posture of the first part to a target position and obtaining the current bone posture of the model to be processed includes the steps of: performing a collision test between the first part and the target object based on the bone posture data of the first part and the target position, and obtaining a collision contact compatible position between the first part and the target object; and correcting the end bone posture of the first part to a position corresponding to the collision contact compatible position, and obtaining the current bone posture of the model to be processed.

[0122] In an exemplary embodiment of the present disclosure, based on the above solution, the target object is a second part of the model to be processed, and the motion spectrum further includes a second part marker of the second part. Correspondingly, the step of correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the model to be processed includes the step of correcting the terminal bone posture of the first part to a position corresponding to the second part marker and obtaining the current bone posture of the model to be processed.

[0123] In an exemplary embodiment of the present disclosure, based on the above solution, the pre-defined vital parts include at least one of the head, limbs, buttocks, and shoulders.

[0124] In an exemplary embodiment of the present disclosure, a computer-readable signal medium is provided, Reference pivotal bone orientation data and intermediate bone orientation data of the model to be processed are acquired, and a bone orientation of the model to be processed is generated based on the reference pivotal bone orientation data and the intermediate bone orientation data.

[0125] In the computer-readable signal medium provided by the embodiments of the present disclosure, pivotal bone posture data of preset pivotal parts including different movements is pre-arranged based on a reference model. When determining bone posture data for any type of target model, first, each preset pivotal part in the current movement of the target model is identified, and then, target pivotal bone posture data of each preset pivotal part in the current movement is extracted from the movement spectrum. Then, based on the target pivotal bone posture data, intermediate bone posture data of other bones other than the preset pivotal part bones in the target model are simply determined, thereby obtaining bone data for all bones in the target model. According to the first aspect, the reference model enables different movements to be mapped to different target models, thereby avoiding the need to redevelop the same movement multiple times in different models, and greatly reducing the amount of work required for animation development, thereby solving the current technical problem of time-consuming animation creation and achieving the technical effects of reducing animation creation time and creation costs. According to the second aspect, the embodiments of the present disclosure store key bone posture data of preset key parts of the reference model based on the movement spectrum, thereby greatly saving storage space compared to the conventional situation of storing all key bone posture data for different movement frames of different models.

[0126] A program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (non-limiting list) of readable storage media include an electrical connection, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0127] A computer-readable signal medium may include a propagated data signal, either contained in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium may be any readable medium other than a readable storage medium that can transmit, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0128] The program code contained in the readable medium may be transmitted over any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0129] Program code for performing operations of the present disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can execute entirely on the user computing device, partially on the user device, as a separate package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. When referring to a remote computing device, the remote computing device can be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider). In an embodiment of the present disclosure, program code stored in a computer-readable storage medium, when executed, can realize any step of the bone pose data determination method or bone pose determination method described above.

[0130] 12, an exemplary embodiment of the present disclosure further provides an electronic device 1200, which may be a spool server of an information platform. The electronic device 1200 will be described with reference to FIG. 12. It should be understood that the electronic device 1200 shown in FIG. 12 is merely an example and does not impose any limitations on the functionality and scope of use of the embodiments of the present disclosure.

[0131] 12, electronic device 1200 is depicted as a general-purpose computing device. Components of electronic device 1200 may include, but are not limited to, at least one processing unit 1210, at least one storage unit 1220, and a bus 1230 connecting different system components (including storage unit 1220 and processing unit 1210).

[0132] Here, the storage unit stores program code, which may be executed by the processing unit 1210 to execute steps of various exemplary embodiments of the present disclosure described in the "Exemplary Method" section above. For example, the processing unit 1210 may execute the following steps shown in FIG. 1 : identifying each preset pivotal part in a current motion of a target model; extracting reference pivotal bone posture data of each preset pivotal part in the current motion from a pre-arranged motion spectrum to obtain target pivotal bone posture data of each preset pivotal part of the target model; and determining intermediate bone posture data of bones other than the preset pivotal part bones of the target model based on the target pivotal bone posture data and the target model.

[0133] In an exemplary embodiment of the present disclosure, based on the above solution, before extracting reference pivotal bone posture data of each preset pivotal part in a current movement from a pre-arranged movement spectrum and obtaining target pivotal bone posture data of each preset pivotal part of a model to be processed, the bone posture data determination method further includes the steps of obtaining movement postures of the reference model in different movements, extracting reference pivotal bone posture data of each preset pivotal part in a movement posture for each movement, and generating a movement spectrum based on each reference pivotal bone posture data corresponding to each movement.

[0134] In an exemplary embodiment of the present disclosure, based on the above solution, the step of extracting reference pivotal bone posture data of each preset pivotal part in the current movement from the pre-arranged motion spectrum and obtaining target pivotal bone posture data of each preset pivotal part of the model to be processed includes the steps of: extracting reference pivotal bone posture data of each preset pivotal part in the current movement from the pre-arranged motion spectrum and obtaining initial pivotal bone posture data of each preset pivotal part of the model to be processed; determining a body shape scaling ratio of the model to be processed relative to the reference model based on the reference body shape data of the reference model and the current body shape data of the model to be processed; and proportionally correcting the initial pivotal bone posture data based on the body shape scaling ratio to obtain target pivotal bone posture data of each preset pivotal part of the model to be processed.

[0135] In an exemplary embodiment of the present disclosure, based on the above solution, before determining the body shape scaling ratio of the target model to the reference model based on the reference body shape data of the reference model and the current body shape data of the target model, the bone posture data determination method further includes a step of determining body shape parameters in a preset reference posture of the reference model and obtaining reference body shape data, and a step of determining body shape parameters in a preset reference posture of the target model and obtaining current body shape data.

[0136] In an exemplary embodiment of the present disclosure, based on the above solution, the step of determining intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed based on the target pivotal bone posture data and the model to be processed includes: determining end position information of each preset pivotal part of the model to be processed; and solving the bone postures of bones other than the preset pivotal bones in the model to be processed by an inverse kinematics algorithm based on the end position information and the target pivotal bone posture data, to obtain intermediate bone posture data.

[0137] In an exemplary embodiment of the present disclosure, based on the above solution, the step of determining intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed based on the target pivotal bone posture data and the model to be processed includes the steps of inputting the target pivotal bone posture data into a bone posture determination model to obtain intermediate bone posture data of bones other than the preset pivotal bones in the model to be processed, and the bone posture determination model is trained based on the bone posture data of the model to be processed in different movements.

[0138] In an exemplary embodiment of the present disclosure, based on the above solution, the motion spectrum further includes a motion paraphrase for each motion, and the motion paraphrase is set to indicate the motion content of the current motion. The bone posture data determination method further includes: extracting a target motion paraphrase corresponding to the current motion from the motion spectrum; and posture correcting the target key bone posture data and intermediate bone posture data based on the target motion paraphrase to obtain target bone posture data of the model to be processed.

[0139] In an exemplary embodiment of the present disclosure, based on the above solution, when the current motion is a contact fit between a first part of the model to be processed and a target object, the step of posture correcting the target pivotal bone posture data and the intermediate bone posture data based on the target motion paraphrase and obtaining the target bone posture data of the model to be processed includes the steps of determining a target position of the target object, correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the model to be processed, and extracting the bone posture data of the current bone posture and obtaining the target bone posture data.

[0140] In an exemplary embodiment of the present disclosure, based on the above solution, the step of correcting the end bone posture of the first part to a target position and obtaining the current bone posture of the model to be processed includes the steps of: performing a collision test between the first part and the target object based on the bone posture data of the first part and the target position, and obtaining a collision contact compatible position between the first part and the target object; and correcting the end bone posture of the first part to a position corresponding to the collision contact compatible position, and obtaining the current bone posture of the model to be processed.

[0141] In an exemplary embodiment of the present disclosure, based on the above solution, the target object is a second part of the model to be processed, and the motion spectrum further includes a second part marker of the second part. Correspondingly, the step of correcting the terminal bone posture of the first part to the target position and obtaining the current bone posture of the model to be processed includes the step of correcting the terminal bone posture of the first part to a position corresponding to the second part marker and obtaining the current bone posture of the model to be processed.

[0142] In an exemplary embodiment of the present disclosure, based on the above scheme, the pre-defined vital parts include at least one of the head, limbs, buttocks, and shoulders.

[0143] Also, for example, the processing unit 1210 may execute step 901 shown in FIG. 9 of acquiring reference pivotal bone posture data and intermediate bone posture data of the model to be processed, and step 902 of generating bone postures of the model to be processed based on the reference pivotal bone posture data and the intermediate bone posture data.

[0144] The electronic device provided by the embodiments of the present disclosure pre-arranges pivotal bone posture data of preset pivotal parts including different movements based on a reference model, and when determining bone posture data for any type of target model, first identifies each preset pivotal part in the current movement of the target model, then extracts target pivotal bone posture data of each preset pivotal part in the current movement from the movement spectrum, and then determines intermediate bone posture data of other bones other than the preset pivotal part bones in the target model based on the target pivotal bone posture data, thereby obtaining bone data for all bones in the target model. According to the first aspect, the reference model enables different movements to be mapped to different target models, thereby avoiding the need to redevelop the same movement multiple times in different models, and greatly reducing the amount of work required for animation development, thereby solving the current technical problem of time-consuming animation creation and achieving the technical effects of reducing animation creation time and creation costs. According to the second aspect, the embodiments of the present disclosure store key bone posture data of preset key parts of the reference model based on the movement spectrum, thereby greatly saving storage space compared to the conventional situation of storing all key bone posture data for different movement frames of different models.

[0145] The storage unit 1220 may include a volatile storage unit, such as a random access storage unit (RAM) 1221 and / or a cache storage unit 1222 , and may also include a read-only storage unit (ROM) 1223 .

[0146] The storage unit 1220 may include, but is not limited to, a program / utility 1224 having a set (at least one) of program modules 1225, including an operating system, one or more applications, other program modules, and program data, each of which, or some combination thereof, may include the implementation of a network environment.

[0147] The bus 1230 may include a data bus, an address bus, and a control bus.

[0148] Electronic device 1200 can communicate with one or more external devices 2000, such as a keyboard, a pointing device, a Bluetooth device, etc., via input / output (I / O) interface 1240. Electronic device 1200 can also communicate with one or more networks, such as a local area network (LAN), a wide area network (WAN), and / or the public network Internet, via network adapter 1250. As shown, network adapter 1250 communicates with other modules of electronic device 1200 via bus 1230. Although not shown, it should be understood that other hardware and / or software modules, including, but not limited to, microcode, device drives, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, etc., can be used in combination with electronic device 1200.

[0149] In an embodiment of the present disclosure, when the program code stored in the electronic device is executed, the steps of either the bone posture data determination method or the bone posture determination method can be realized.

[0150] Although the above detailed description refers to several modules or units of an apparatus for performing operations, such division is not mandatory. In fact, according to exemplary embodiments of the present disclosure, the features and functions of two or more of the above-described modules or units may be embodied in one module or unit. Conversely, the features and functions of one of the above-described modules or units may be further divided and embodied in multiple modules or units.

[0151] Those skilled in the art will appreciate that various aspects of the present disclosure can be embodied as a system, method, or program product. Accordingly, various aspects of the present disclosure can be embodied as an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which may be collectively referred to herein as a "circuit," "module," or "system." Other embodiments of the present disclosure will be readily apparent to those skilled in the art after studying the specification and practicing the invention(s) disclosed herein. The present disclosure is intended to cover any modifications, uses, or adaptations of the present disclosure, which modifications, uses, or adaptations comply with the general principles of the present disclosure and include common knowledge or commonly used technical means in the art that are not disclosed herein. The specification and embodiments should be considered merely as examples, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0152] It should be noted that the present disclosure is not limited to the precise configurations described above and illustrated in the drawings, and various modifications and variations are possible without departing from the spirit and scope of the present disclosure. The scope of the present disclosure is limited only by the appended claims.

Claims

1. identifying each predetermined vital point in the current operation of the model being processed; A step of extracting reference pivotal bone posture data of each of the preset pivotal parts in the current motion from a pre-arranged motion spectrum, and obtaining target pivotal bone posture data of each of the preset pivotal parts of the processing target model, wherein the motion spectrum stores reference pivotal bone posture data of each of the preset pivotal parts in different motions of a reference model; determining intermediate bone posture data of bones other than the predetermined pivotal part bones in the processing object model based on the target pivotal bone posture data and the processing object model, A bone posture data determination method comprising:

2. The bone posture data determination method includes: extracting reference pivotal bone posture data of each of the preset pivotal parts in the current motion from the preset motion spectrum; and before obtaining target pivotal bone posture data of each of the preset pivotal parts of the processing target model, acquiring a motion posture of the reference model in different motions; extracting the reference pivotal bone posture data of each of the predetermined pivotal parts in the movement posture for each movement; generating the motion spectrum based on each of the reference pivotal bone posture data corresponding to each motion; 2. The bone posture data determination method according to claim 1.

3. The step of extracting reference pivotal bone posture data of each of the preset pivotal parts in the current motion from the preset motion spectrum and obtaining target pivotal bone posture data of each of the preset pivotal parts of the processing target model includes: Extracting the reference pivotal bone posture data of each of the preset pivotal parts in the current motion from the pre-arranged motion spectrum, and obtaining the initial pivotal bone posture data of each of the preset pivotal parts of the processing target model; determining a body shape scaling ratio of the processing target model relative to the reference model based on reference body shape data of the reference model and current body shape data of the processing target model; and proportionally correcting the initial pivotal bone posture data based on the body shape scaling ratio to obtain the target pivotal bone posture data of each of the predetermined pivotal parts of the processing target model.

2. The bone posture data determination method according to claim 1.

4. Before determining a body shape scaling ratio of the processing target model to the reference model based on reference body shape data of the reference model and current body shape data of the processing target model, the bone posture data determination method includes: determining body type parameters of the reference model in a preset reference posture to obtain the reference body type data; The bone posture data determination method according to claim 3 , further comprising: determining body shape parameters of the processing target model in the preset reference posture to obtain the current body shape data.

5. 2. The bone posture data determination method according to claim 1, wherein the step of determining intermediate bone posture data of bones other than the predetermined pivotal part bones in the processing target model based on the target pivotal bone posture data and the processing target model comprises the steps of: determining end position information of each of the predetermined pivotal parts of the processing target model; and solving bone postures of bones other than the predetermined pivotal part bones in the processing target model by an inverse kinematics algorithm based on the end position information and the target pivotal bone posture data, thereby obtaining the intermediate bone posture data.

6. 4. The bone posture data determination method of claim 3, wherein the step of determining intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model based on the target pivotal bone posture data and the processing target model comprises the step of inputting the target pivotal bone posture data into a bone posture determination model to obtain the intermediate bone posture data of bones other than the predetermined pivotal bones in the processing target model, and the bone posture determination model is trained based on bone posture data of the processing target model in different movements.

7. 2. The bone posture data determination method of claim 1, wherein the motion spectrum further includes a motion paraphrase for each motion, the motion paraphrase being set to indicate the motion content of a current motion, and the bone posture data determination method further includes: a step of extracting a target motion paraphrase corresponding to the current motion from the motion spectrum; and a step of posture-correcting the target key bone posture data and the intermediate bone posture data based on the target motion paraphrase to obtain target bone posture data of the processing target model.

8. When the current motion is a contact fit between a first portion of the processing target model and a target object, the step of correcting the target pivotal bone posture data and the intermediate bone posture data based on the target motion paraphrase to obtain target bone posture data of the processing target model includes: determining a target position of the target object; correcting the terminal bone posture of the first part to the target position and acquiring the current bone posture of the processing target model; 8. The bone posture data determination method according to claim 7, further comprising: extracting bone posture data of the current bone posture to obtain the target bone posture data.

9. The step of correcting the terminal bone posture of the first part to the target position and acquiring the current bone posture of the processing target model includes: performing a collision test between the first part and the target object based on the bone posture data of the first part and the target position, and obtaining a collision contact compatible position between the first part and the target object; and correcting the terminal bone posture of the first part to a position corresponding to the collision contact compatible position, and obtaining the current bone posture of the processing target model.

10. the target object is a second part of the processing target model, and the motion spectrum further includes a second part marker of the second part; Correspondingly, the step of correcting the terminal bone posture of the first part to the target position and acquiring the current bone posture of the processing target model includes:

9. The bone posture data determination method according to claim 8, further comprising a step of correcting the terminal bone posture of the first part to a position corresponding to the second part marker, and acquiring the current bone posture of the processing target model.

11. The predetermined vital parts include at least one of the head, the limbs, the buttocks, and the shoulders.

11. The bone posture data determination method according to claim 1, wherein the bone posture data determination method is a method for determining a bone posture.

12. a step of acquiring reference pivotal bone posture data and intermediate bone posture data of a processing target model, the reference pivotal bone posture data and the intermediate bone posture data being determined based on a bone posture data determination method according to any one of claims 1 to 11; generating a bone posture of a processing target model based on the reference pivotal bone posture data and the intermediate bone posture data; A bone posture determination method characterized by:

13. A bone pose data determination device comprising an identification module, an extraction module, and a determination module, The identification module is configured to identify each predetermined vital point in the current operation of the processed model; The extraction module is configured to extract reference pivotal bone posture data of each of the preset pivotal parts in the current motion from a pre-arranged motion spectrum, and obtain target pivotal bone posture data of each of the preset pivotal parts of the processing target model, wherein the motion spectrum stores reference pivotal bone posture data of each of the preset pivotal parts in different motions of a reference model; the determination module is configured to determine intermediate bone posture data of bones other than the predetermined pivotal part bones in the processing object model based on the target pivotal bone posture data and the processing object model; A bone posture data determination device characterized by:

14. A bone pose determination device comprising: an acquisition module; and a generation module, the acquisition module is configured to acquire reference pivotal bone posture data and intermediate bone posture data of a processing target model, the reference pivotal bone posture data and the intermediate bone posture data being determined based on a bone posture data determination method according to any one of claims 1 to 11; the generation module is configured to generate a bone posture of a processing target model based on the reference pivotal bone posture data and the intermediate bone posture data; A bone attitude determination device characterized by:

15. A computer-readable storage medium on which a computer program is stored, When the computer program is executed by a processor, the method according to any one of claims 1 to 12 is realized. A computer-readable storage medium comprising:

16. An electronic device comprising a processor and a memory, the memory is configured to store executable instructions for the processor; The processor is configured to perform the method of any one of claims 1 to 12 by executing the executable instructions. An electronic device characterized by:

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