CN114627274A

CN114627274A - Object processing method and device

Info

Publication number: CN114627274A
Application number: CN202210259063.3A
Authority: CN
Inventors: 王爽; 刘马良; 李爱华; 张其珍; 潘亚楠
Original assignee: Guangzhou Xishanju Network Technology Co ltd; Zhuhai Kingsoft Digital Network Technology Co Ltd
Current assignee: Guangzhou Xishanju Network Technology Co ltd; Zhuhai Kingsoft Digital Network Technology Co Ltd
Priority date: 2022-03-16
Filing date: 2022-03-16
Publication date: 2022-06-14

Abstract

The application provides an object processing method and device, wherein the object processing method comprises the following steps: adjusting the object parameters of the initial object through the parameter adjustment ratio based on the object acquisition request to obtain a candidate object after parameter adjustment; determining a similarity result of the initial object and the candidate object; and determining the candidate object as the target object under the condition that the similarity result meets the object similarity condition. Therefore, the purpose of automatically generating the target object is achieved, the problem that the workload of the art personnel is increased greatly due to the fact that models with different definitions need to be manufactured by the art personnel is solved, the workload of the art personnel is reduced, and the cost of game development is further reduced.

Description

Object processing method and device

Technical Field

The application relates to the technical field of game development, in particular to an object processing method. The application also relates to an object processing apparatus, a computing device, and a computer-readable storage medium.

Background

With the continuous development of game development technology, the game can be run on a plurality of devices, and the user base number of the game is directly determined. Therefore, many game manufacturers optimize games to increase the number of users of the games, run the games on a wider variety of devices as much as possible, and display the best effect of the games with the lowest power consumption as possible.

In the prior art, a plurality of game manufacturers display models with different definitions according to the distance between a camera and a game model, and the more distant the camera is, the less precise the model is displayed; therefore, the rendering pressure is reduced under the condition of not reducing the visual effect, and the game performance is improved. However, in the practical application process, model resources with different definitions need to be manufactured by art workers, so that the workload of the art workers is greatly increased, and the game development cost is increased.

Disclosure of Invention

In view of this, an embodiment of the present application provides an object processing method to solve technical defects in the prior art. The embodiment of the application also provides an object processing device, a computing device and a computer readable storage medium.

According to a first aspect of embodiments of the present application, there is provided an object processing method, including:

adjusting the object parameters of the initial object through the parameter adjustment ratio based on the object acquisition request to obtain a candidate object after parameter adjustment;

determining a similarity result of the initial object and the candidate object;

and determining the candidate object as a target object under the condition that the similarity result meets an object similarity condition.

According to a second aspect of embodiments of the present application, there is provided an object processing apparatus including:

the adjusting module is configured to adjust the object parameters of the initial object through a parameter adjusting ratio based on the object obtaining request to obtain parameter-adjusted candidate objects;

a result determination module configured to determine a similar result of the initial object to the candidate object;

an object determination module configured to determine the candidate object as a target object if the similarity result satisfies an object similarity condition.

According to a third aspect of embodiments herein, there is provided a computing device comprising:

a memory and a processor;

the memory is for storing computer-executable instructions that when executed by the processor implement the steps of the object processing method.

According to a fourth aspect of embodiments herein, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the object processing method.

According to a fifth aspect of embodiments of the present application, there is provided a chip storing a computer program which, when executed by the chip, implements the steps of the object processing method.

The object processing method provided by the application adjusts the object parameters of the initial object through the parameter adjustment ratio based on the object acquisition request to obtain the candidate object after parameter adjustment; determining a similarity result of the initial object and the candidate object; and determining the candidate object as the target object under the condition that the similarity result meets the object similarity condition.

Specifically, the object processing method automatically adjusts the initial object based on the parameter adjustment ratio to obtain the candidate object under the condition that the object acquisition request for the target object is received, and determines the candidate object as the target object under the condition that the similarity result of the initial object and the candidate object meets the object similarity condition, so that the aim of automatically generating the target object is fulfilled, the problem that the workload of art workers is increased greatly due to the fact that models with different definitions need to be manufactured by the art workers is solved, the workload of the art workers is reduced, and the cost of game development is further reduced.

Drawings

Fig. 1 is a flowchart of an object processing method according to an embodiment of the present application;

FIG. 2 is a processing flow diagram of an object processing method applied in a scenario of automatically generating multi-detail-level resources according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an object processing apparatus according to an embodiment of the present application;

fig. 4 is a block diagram of a computing device according to an embodiment of the present application.

Detailed Description

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of implementation in many different ways than those herein set forth and of similar import by those skilled in the art without departing from the spirit of this application and is therefore not limited to the specific implementations disclosed below.

The terminology used in the one or more embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the present application. As used in one or more embodiments of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present application refers to and encompasses any and all possible combinations of one or more of the associated listed items.

It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments of the present application to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first aspect may be termed a second aspect, and, similarly, a second aspect may be termed a first aspect, without departing from the scope of one or more embodiments of the present application.

First, the noun terms to which one or more embodiments of the present invention relate are explained.

Level of Detail (LOD, Levels of Detail): is a technique for optimizing game resources.

LOD resources: a plurality of models of different fineness are displayed for one game object (game object or game character) at different camera distances.

Simplygon: is a platform with which 3D material, such as models and textures, can be optimized for different purposes.

Polygon Cruncher: A3D model face reduction tool.

3ds Max: is 3D modeling rendering and manufacturing software.

Pixel: is a minimum unit in an image represented by a sequence of numbers, each pixel having a distinct location and assigned color value, the color and location determining how the image appears.

With the continuous development of game development technology, in the current era, a game can run on a plurality of devices, and the user base number of the game is directly determined, so that many game manufacturers need to make game optimization, run the game on more devices as much as possible, and display the optimal effect with the lowest power consumption as much as possible, thereby achieving the purpose of increasing the user amount.

Therefore, many game manufacturers may adopt a multi-level of detail technology, which is a technology for optimizing game resources, to display models of different levels according to the distance of a camera from the models, and to display models with lower fineness the farther the camera is, thereby reducing rendering pressure and improving game performance without reducing visual effect.

However, because each resource (game object or game role) needs to make a plurality of LOD resources, and meanwhile, it is also ensured that visual effects are not affected when one model switches LOD resources of different levels, the workload of art workers is greatly increased, and the cost of game development is further increased.

Based on this, in the present application, an object processing method is provided. The present application relates to an object processing apparatus, a computing device, and a computer-readable storage medium, which are described in detail in the following embodiments one by one.

Fig. 1 is a flowchart of an object processing method according to an embodiment of the present application, which specifically includes the following steps.

Step S102: and adjusting the object parameters of the initial object through the parameter adjustment ratio based on the object acquisition request to obtain the candidate object after parameter adjustment.

When the object processing method is applied to a game scene, the initial object may be understood as an object that needs to generate a corresponding LOD resource in a game, and specifically, the initial object may be a model in the game. For example, the initial object may be a game character model, a game item model, a game scene model, or the like.

Accordingly, the object acquisition request may be understood as a request for generating the LOD resource corresponding to the initial object. Accordingly, the target object can be understood as the LOD resource corresponding to the initial object. For example, where the initial model is an original "tree" model in the game, the target object may be a "tree" model of different fineness corresponding to the "tree" model. Wherein the target object may be less fine than the initial object. In practical applications, a multi-level of detail (LOD) technique can display different levels of "tree" models based on how far the "tree" models are from the camera. The tree models at different levels are LOD resources. For example, when the distance between the "tree" model and the camera is 0 meter, the "tree" model at the first level (with the highest fineness) among the "tree" models at different levels is displayed to the game player; when the distance between the tree model and the camera is more than 10 meters and less than or equal to 50 meters, the tree model at the second level in the tree models at different levels is displayed to a game player; in the case where the distance between the tree model and the camera is greater than 50 meters, the tree model at the third level (with the lowest fineness) of the tree models at different levels is shown to the game player. It should be noted that the LOD resource corresponding to the initial object may be formed by the initial object and the target object; the initial object can be created by the art personnel; the fineness of the initial object is greater than that of the target object. Wherein the fineness of the initial object can be understood as the total number of faces of the game model.

When the object processing method is applied to a game scene, the object parameters can be understood as parameters of game objects and can realize optimization of a game after adjustment. For example, the object parameter may be understood as the total number of faces of the game model.

In the case where the object parameter is the total number of faces of the model, the parameter adjustment ratio may be understood as a ratio at which the total number of faces needs to be reduced during the face reduction operation for the total number of faces of the model. It should be noted that the parameter adjustment ratio may be set according to an actual application scenario, for example, the reduction ratio may be 30%, 50%, or the like.

Accordingly, the candidate object can be understood as a face-reducing game model obtained after the face-reducing operation is performed through the parameter adjustment ratio, and in practical application, the face-reducing game model after the face-reducing operation is performed can be used as a temporary LOD resource.

Specifically, the object processing method provided by the present specification is capable of receiving an object acquisition request for a target object, and after receiving the object acquisition request, adjusting an object parameter of an initial object based on a parameter adjustment ratio in response to the object acquisition request, and acquiring a parameter-adjusted candidate object. In practical applications, the object fetching request may be an instruction sent by any resource fetching object that needs to fetch the LOD resource. The resource acquisition object may be set according to an actual application scenario, which is not specifically limited in this specification, for example, the resource acquisition object may be an intelligent device, an artificial intelligence robot, an application program, and the like.

Taking the application of the object processing method in automatically generating a multi-detail level resource (LOD resource) scene as an example, the following further explains the receiving of an object acquisition request for a target object. Wherein, the initial object can be a high-precision tree model made by an art designer; the target object is a low-precision tree model corresponding to the high-precision tree model. Namely, the resource (LOD resource) of multiple detail levels corresponding to the high-precision tree model; the high accuracy can be understood as a high number of faces of the model, and correspondingly, the high accuracy can be understood as a low number of faces of the model. The object acquisition request may be an LOD resource generation request, the object parameter may be a total number of faces of the game model, the candidate object may be a temporary LOD resource, and the object adjustment ratio may be a face reduction ratio (30%), based on which the object processing method provided in the present specification may automatically perform, in response to the LOD resource generation request, generation of the temporary LOD resource by reducing the number of faces of the high-precision "tree" model by 30% based on the face reduction ratio (30%) in response to the LOD resource generation request.

In an embodiment provided in this specification, a face reduction operation is performed on a model based on a face reduction ratio and a reduction tool, so as to improve the efficiency of model reduction, and the specific implementation manner is as follows.

The method for obtaining the candidate object after parameter adjustment by adjusting the object parameter of the initial object according to the parameter adjustment ratio based on the object obtaining request comprises the following steps:

receiving an object acquisition request aiming at a target object, wherein the object acquisition request carries an initial object corresponding to the target object;

determining a parameter adjustment ratio corresponding to the initial object;

and adjusting the object parameters of the initial object through the parameter adjustment ratio based on a parameter adjustment module to obtain the candidate object after parameter adjustment.

The parameter adjusting module may be understood as a module that adjusts an object parameter of an initial object, for example. In the case that the object parameter is the total number of faces of the game model, the parameter adjusting module may be a face reduction tool that reduces the total number of faces of the game model. It should be noted that the face reduction tool may be set according to the needs of an actual application scenario, and this specification does not specifically limit this, for example, the face reduction tool may be a Simplygon tool, a Polygon Cruncher, a 3ds max, or the like.

Specifically, the object processing method provided in this specification can determine, in response to an object acquisition request after receiving the object acquisition request, a parameter adjustment ratio corresponding to the initial object, where the parameter adjustment ratio can be set according to an actual scene. And then, based on a parameter adjusting module, adjusting the object parameters of the initial object carried in the object obtaining request according to the parameter adjusting ratio to obtain the candidate object after parameter adjustment.

Following the above example, wherein the parameter adjustment module is a Simplygon tool, the object parameter is the total number of faces of the game model, and the candidate object is a temporary LOD resource. Based on this, when an LOD resource generation request is received, in response to the LOD resource generation request, a reduction ratio (30% reduction) corresponding to the high-precision "tree" model is determined, and then a Simplygon tool is used to perform a 30% reduction operation on the high-precision "tree" model (original model) having the number of faces of 1000 based on the reduction ratio, and reduce the number of faces of the original model by 30%, thereby generating a temporary LOD resource (a "tree" model having the number of faces of 700).

In the embodiment provided by the present specification, the object parameter of the initial object can be adjusted through the parameter adjustment ratio corresponding to the initial object based on the parameter adjustment module automatically, so as to obtain the candidate object after the parameter adjustment. Therefore, the model is reduced in an automatic mode, the workload of art workers is reduced, and the efficiency of subsequently generating LOD resources is further improved.

Step S104: determining a similarity result of the initial object and the candidate object.

In practical application, in the process of generating the LOD resources corresponding to the game object, in order to ensure that the effect of the generated LOD resources is optimal and that the smooth switching between different LOD resources is performed in the process of subsequently switching different LOD resources when the distance between the model and the camera is different, the visual effect of the game is not affected. Therefore, it is necessary to determine the similarity between the original model and the temporary LOD resource after the face reduction operation is performed on the original model. And the LOD resource with the optimal visual effect can be obtained based on the similarity conveniently.

Specifically, after the candidate object is determined, the result of similarity between the initial object and the candidate object can be determined. Wherein the similarity result can be understood as a result representing the degree of similarity between the initial object and the candidate object. For example, the similarity result may be a similarity degree; the degree of acquaintance may be any value within the interval [0,1], where a value of 0 indicates the least similarity between the initial object and the candidate object and a value of 1 indicates the most similarity between the initial object and the candidate object. Alternatively, the similarity result may be a label that characterizes whether the initial object and the candidate object are similar, for example, the similarity result may be a "similar label" or a "dissimilar label".

In an embodiment provided in this specification, to ensure accuracy of a similar result between the original model and the temporary LOD resource, before determining the original model and the temporary LOD resource, the original model and the temporary LOD resource may be adjusted based on the model screen occupation ratio to obtain the original model and the temporary LOD resource in the same screen occupation ratio. Subsequently, determining a similar result of the original model and the temporary LOD resource under the same screen occupation ratio, thereby ensuring the accuracy of the similar result; the specific implementation is as follows.

Before the determining the similarity between the initial object and the candidate object, the method further includes:

determining an object display ratio corresponding to the target object;

and adjusting the display ratio of the initial object and the candidate object based on the object display ratio to obtain the initial object after the display ratio is adjusted and the candidate object after the display ratio is adjusted.

Wherein, the object display ratio can be understood as the ratio of model screens. In practical applications, the difference in distance between the model and the camera may cause the proportion of the model in the game screen to be different. Therefore, the model screen ratio has a corresponding relationship with the distance between the model and the camera. The model screen fraction may vary correspondingly as the model is moved closer to or further from the camera. It should be noted that the model screen ratio may be configured by the resource acquisition object in the process of generating the target object. For example, the object processing method provided in this specification can receive a configuration instruction for a model screen proportion sent by a resource obtaining object, where the configuration instruction carries the model screen proportion that the resource obtaining object needs to configure, and the model screen proportion carried in the configuration instruction may be 30%.

Specifically, the object processing method provided by the present specification can determine an object display ratio corresponding to the target object after obtaining the candidate object; and adjusting the display ratio of the initial object and the candidate object based on the object display ratio to obtain the initial object after the display ratio is adjusted and the candidate object after the display ratio is adjusted.

Along with the above example, the object display ratio is the model screen ratio. Based on this, after the temporary LOD resource is generated, the screen occupation ratio of the temporary LOD resource and the original resource (original model) can be set based on the pre-configured LOD model screen occupation ratio, and the original model and the temporary LOD resource under the same screen occupation ratio can be obtained.

In an embodiment provided by this specification, in a process of determining a similarity result between a temporary LOD resource and an original model, an object processing method provided by this specification may collect images of the LOD resource and the original model respectively, and determine a similarity between the LOD resource and the original model based on the collected images, which is specifically implemented as follows.

The determining the similarity between the initial object and the candidate object includes steps S1042 to S1046:

step S1042: at least two first images of the initial object are acquired based on at least two image acquisition perspectives, and at least two second images of the candidate object are acquired.

The image capturing view angle may be understood as a view angle for capturing at least two first images and at least two second images in multiple directions, for example, the image capturing view angle may be a front view, a rear view, a top view, a bottom view, a left view, a right view, and the like. Accordingly, the first image can be understood as a model view of the game model under a plurality of collection visual angles; this second image may be understood as a model view of the temporary LOD asset at multiple acquisition perspectives.

According to the above example, based on the multi-azimuth photographing view angle, image acquisition is performed on the original model and the temporary LOD resource, and a multi-azimuth model view corresponding to the original model and a multi-azimuth model view corresponding to the temporary LOD resource are obtained. The multi-azimuth model view corresponding to the original model comprises a front view, a rear view, a top view, a bottom view, a left view and a right view of the original model. Correspondingly, the multi-azimuth model view corresponding to the temporary LOD resource comprises a main view, a rear view, a top view, a bottom view, a left view, a right view and the like of the temporary LOD resource.

Step S1044: and establishing an association relation between each first image and each second image based on the at least two image acquisition visual angles.

Specifically, the establishing of the association relationship between each first image and each second image based on the at least two image acquisition perspectives includes:

determining an image acquisition perspective for each first image and determining an image acquisition perspective for each second image;

determining a second image in each second image, which has the same image acquisition view angle as that of each first image, as a second image associated with each first image;

and determining the association relationship between each first image and each second image based on each first image and the second image associated with each first image.

According to the above example, the acquisition visual angle corresponding to each view in the multi-azimuth model views corresponding to the original model is determined; and determining the acquisition visual angle corresponding to each view in the multi-azimuth model view corresponding to the temporary LOD resource. And determining the view which belongs to the same acquisition view angle as the view of the original model in the multi-azimuth model view corresponding to the temporary LOD resource as the view associated with the view of the original model.

And constructing an incidence relation between the multi-azimuth model view corresponding to the original model and the multi-azimuth model view corresponding to the temporary LOD resource based on the view of the original model and the view associated with the view of the original model in the multi-azimuth model view corresponding to the temporary LOD resource.

In an embodiment provided by the present specification, an image capturing perspective of each first image is determined, and an image capturing perspective of each second image is determined; and determining the association relationship between each first image and each second image based on the same image acquisition view angle. The method facilitates the subsequent determination of the similar result between the initial object and the candidate object based on the incidence relation, and improves the effect of the target object.

Step S1046: determining a similarity result of the initial object and the candidate object based on the each first image, the each second image and the association relation.

Further, the determining a similarity result of the initial object and the candidate object based on the each first image, the each second image and the association relationship includes:

determining a second image associated with each first image from each second image based on the association relation;

determining an image similarity between each first image and the associated second image based on the pixel information of each pixel in each first image and the pixel information of each pixel in the associated second image;

determining the similarity of the initial object and the candidate object based on the image similarity.

Wherein the pixel information can be understood as the color value assigned to the pixel. Accordingly, the image similarity may be understood as a numerical value representing the degree of similarity between the first image and the second image. For example, the similarity may be any value within the interval [0,1], where a value of 0 indicates the least similar and a value of 1 indicates the most similar.

Determining a view of the same acquisition visual angle from the multi-azimuth model view of the original model and the multi-azimuth model view of the temporary LOD resource based on the incidence relation between the multi-azimuth model view of the original model and the multi-azimuth model view of the temporary LOD resource; the view may be a front view.

Based on this, the color value of each pixel in the main view of the original model and the color value of each pixel in the main view of the temporary LOD resource are determined. And determining the image similarity of the main view of the original model and the main view of the temporary LOD resource based on the difference of the color value of each pixel in the two main views.

In order to avoid redundant description, the image similarity between the original model and other views of the temporary LOD resource can refer to the processing step of the main view, so as to obtain the image similarity between the original model and the temporary LOD resource and between all the views at the same acquisition view angle. For example, the image similarity between the left view of the original model and the left view of the temporary LOD resource; image similarity between the right view of the original model and the right view of the temporary LOD resource, and the like.

After determining the image similarity of all the views of the original model and the temporary LOD resource, determining the average value of the image similarity, and taking the average value as the similarity of the original model and the temporary LOD resource. For example, the image similarity between the orientation model view of the original model and the multi-orientation model of the temporary LOD resource is respectively 0.7, 0.8, 0.5, 0.6, 0.8, and 0.9. Taking the average value (equal to 0.7 point) of all image similarities; this 0.7 point is taken as the similarity between the original model and the temporary LOD resource.

In embodiments provided by the present specification, the similarity between the initial object and the candidate object is determined based on the image similarity determined by the pixel information of each pixel in each first image and the pixel information of each pixel in the associated second image. Therefore, the LOD resources with the optimal effect can be obtained based on the similarity, smooth switching among different LOD resources is ensured in the process that different LOD resources are required to be switched at different distances between the model and the camera, and the visual effect of the game is not influenced.

Further, the determining the image similarity between each first image and the associated second image based on the pixel information of each pixel in each first image and the pixel information of each pixel in the associated second image comprises:

determining pixel information for each first pixel in said each first image and for each second pixel in said associated second image;

comparing the pixel information of each first pixel with the pixel information of each second pixel to determine a pixel difference value of each first pixel and each second pixel;

determining an image similarity between each first image and the associated second image based on the pixel difference values of the each first pixel and the each second pixel.

The pixel difference value can be understood as a value representing the similarity between pixels, for example, the value can be any value in the [0,1] interval.

Following the above example, the color value of each pixel in the primary view of the original model and the color value of each pixel in the primary view of the temporary LOD resource are determined. Comparing the color value of each pixel in the view with the color value of each pixel in the main view to determine a pixel difference value X between each pixel in the two views; wherein, when there are 100 pixels in the front view, the number of the pixel difference values X is also 100. And taking the average value of 100 pixel difference values X, and taking the average value of 100 pixel difference values X as the image similarity of the two main views, so that the similarity between the original model and the temporary LOD resource can be accurately determined based on the image similarity.

To avoid redundant description, the processing steps of the main view may be referred to for the image similarity between the original model and the other views of the temporary LOD resource.

In addition, in practical applications, in order to improve the efficiency of determining the similarity between the original model and the temporary LOD resource, the object processing method provided in the present specification may perform difference comparison on opaque pixels in the view of the original model and the view of the temporary LOD resource, and does not perform difference comparison on transparent pixels, thereby improving the efficiency of determining the similarity.

The object processing method provided by the present specification acquires at least two first images of an initial object and at least two second images of candidate objects based on at least two image acquisition perspectives, and establishes an association relationship between each first image and each second image; and determining a similarity result of the initial object and the candidate object based on each first image, each second image and the association relation. And the target object with the best display effect can be accurately determined based on the similar result. The smooth switching among different LOD resources is ensured in the process of switching different LOD resources, and the visual effect of the game is not influenced.

Step S106: and determining the candidate object as the target object under the condition that the similarity result meets an object similarity condition.

The object similarity condition may be set according to an actual application scenario, which is not specifically limited in this specification; for example, in the case where the similar result is a tag, satisfying the object similarity condition may be that the tag is "similar". Accordingly, not satisfying the satisfied object similarity condition may be that the tag is "not similar". Wherein the label may be determined based on a similarity between the initial object and the target object. And determining that the similarity result of the initial object and the target object is a 'similar' label under the condition that the acquaintance degree is greater than a preset threshold value. Otherwise, it is a "dissimilar" label. The preset threshold may be set according to an actual application scenario, which is not specifically limited in this specification. For example, 0.6 point.

Alternatively, in the case where the similarity result is a similarity, the object similarity condition may be understood as a similarity threshold. Accordingly, satisfying the object similarity condition may be understood as the similarity being equal to the similarity threshold. The specific implementation is as follows.

Determining the candidate object as a target object when the similarity result satisfies an object similarity condition, including:

determining the similarity of the initial object and the candidate object based on the similarity result;

determining the candidate object as a target object if the similarity is equal to an object similarity threshold.

It should be noted that the object similarity threshold may be configured by the resource acquisition object in the process of generating the target object. For example, the object processing method provided in this specification can receive a configuration instruction for an object similarity threshold sent by a resource acquisition object, where the configuration instruction carries an object similarity threshold that the resource acquisition object needs to configure, and the object similarity threshold carried in the configuration instruction may be 0.7 minutes.

Along the above example, when the object similarity threshold is 0.7 point, and the similarity (0.7 point) between the original model and the temporary LOD resource is equal to 0.7 point, the temporary LOD resource is determined to be the LOD resource with the optimal performance, so as to obtain the LOD resource corresponding to the original model.

In the object processing method provided by the specification, in the case of receiving an object acquisition request for a target object, an initial object carried in the object acquisition request is automatically adjusted based on a parameter adjustment module to obtain a candidate object, and a similarity result between the initial object and the candidate object is determined, and then the similarity result can be used as a similarity between the initial object and the candidate object, and the candidate object is determined as the target object in the case of determining that the similarity satisfies an object similarity condition, so that the purpose of automatically generating the target object is achieved, the problem that the workload of an art worker is greatly increased due to the fact that models with different definitions need to be manufactured by the art worker is avoided, the workload of the art worker is reduced, and the cost of game development is further reduced.

In an embodiment of the present specification, in the process of determining the optimal LOD resource, an LOD resource whose similarity is equal to a preset similarity threshold and whose parameter adjustment ratio is the minimum may be selected, so as to improve performance of the LOD resource, and a specific implementation manner is as follows.

determining an initial similarity of the initial object and the candidate object based on the similarity result;

determining the initial similarity which is equal to the threshold value of the object similarity as the target similarity;

determining parameter adjustment ratios corresponding to the target similarity, and determining a minimum parameter adjustment ratio from the parameter adjustment ratios;

and determining the candidate object corresponding to the minimum parameter adjustment ratio as a target object.

In practical application, the parameter adjustment ratio can be set to be various different ratios according to different practical application scenes; the initial object is adjusted based on a plurality of parameter adjustment ratios, a plurality of different candidate objects can be obtained, and therefore, the similarity between the initial object and the candidate objects can also include a plurality. Based on this, in the case that the similarity result may be the similarity, the initial similarity of the initial object and the candidate object may be understood as obtaining the degree of acquaintance between the candidate object and the initial object based on the different parameter adjustment ratios.

The target similarity may be understood as an initial similarity equal to the object similarity threshold.

In addition, in the case where the difference in the object parameter between the initial object and the candidate object is small, there can be a case where a plurality of parameter adjustment ratios correspond to the same similar result. For example, the reduction ratio may be 30.5%, 30.4%. In the case where the difference between the face reduction ratios is small, the LOD resources obtained by performing the face reduction operation on the high-precision "tree" model (original model) with 1000 faces by the face reduction ratio may be 0.7 point in similarity with the original model.

In this way, in the object processing method provided in the present specification, the initial similarity between the initial object and the candidate object can be determined based on the result of similarity between the initial object and the candidate object, and the initial similarity equal to the object similarity threshold value can be determined as the target similarity. Then determining a parameter adjustment ratio corresponding to the target similarity, and determining a minimum parameter adjustment ratio from the parameter adjustment ratios; and determining the candidate object corresponding to the minimum parameter adjustment ratio as the target object.

Along with the above example, the reduction ratio can be set to 30.5% and 30.4% according to different practical application scenarios; since the original model is adjusted based on 30.5% and 30.4%, a plurality of different temporary LOD resources can be obtained, and thus, the similarity between the original model and the temporary LOD resources may include a plurality of similarities. Meanwhile, in the case where the difference in the face reduction ratio is small, the degree of similarity between the temporary LOD resource obtained by performing the face reduction operation on the high-precision "tree" model (original model) having 1000 faces by the face reduction ratios of 30.5% and 30.4% and the original model may be 0.7 point.

Based on the similarity, the similarity between the original model and the temporary LOD resources is determined, the similarity which is equal to the object similarity threshold value of 0.7 point is determined, and one or more face reduction ratios corresponding to the similarity are determined. Determining a minimum reduction ratio from the reduction ratios; and determining the temporary LOD resource with the similarity equal to the object similarity threshold value of 0.7 and the face reduction ratio being the minimum as the LOD resource with the optimal performance.

In the embodiment provided in this specification, when the similarity is greater than or less than the object similarity threshold, it indicates that the temporary LOD resource is not the LOD resource with the optimal performance, and therefore, the facet-reduction ratio needs to be adjusted to find an optimal facet-reduction ratio, so that based on the optimal facet-reduction ratio, an LOD resource with the lowest facet number and without affecting the visual effect is generated; the specific implementation is as follows.

After determining the similarity between the initial object and the candidate object, the method further includes:

under the condition that the similarity result does not meet the object similarity condition, adjusting the parameter adjustment ratio based on a preset ratio adjustment rule to obtain an adjusted parameter adjustment ratio;

and continuing to execute the object-based acquisition request, adjusting the object parameters of the initial object through the parameter adjustment ratio, and acquiring the candidate object after parameter adjustment until the similarity result meets the object similarity condition.

When the similarity result is a similarity and the object similarity condition is an object similarity threshold, it can be understood that the similarity result does not satisfy the object similarity condition, and the similarity is greater than the object similarity threshold or the similarity is less than the object similarity threshold.

Accordingly, the preset ratio adjustment rule may be understood as a rule for adjusting the parameter adjustment ratio; the preset ratio adjustment rule can be set according to an actual application scene; for example, the preset ratio adjustment rule may be to adjust the parameter adjustment ratio up by 1% in a case where the similarity is greater than the object similarity threshold. Or in the case that the similarity is smaller than the object similarity threshold, the parameter adjustment ratio is adjusted downward by 1%.

Following the above example, after determining the similarity between the original model and the temporary LOD resource, the face reduction ratio is adjusted up by 1% if the similarity is greater than the object similarity threshold. Or, in the case that the similarity is smaller than the object similarity threshold, the face reduction ratio is adjusted downward by 1%. Thereby obtaining an adjusted reduction ratio. And (3) subtracting the original model by using a face subtraction tool (Simplygon tool) based on the adjusted face subtraction ratio to obtain a new temporary LOD resource, and continuing to perform the operation of determining the similarity between the original model and the new temporary LOD resource until the similarity between the original model and the temporary LOD resource is equal to the object similarity threshold. It is determined to find an optimal reduction ratio and the resource generated using the reduction ratio is used as the LOD resource.

In the embodiment provided in this specification, because the optimal LOD resource may be determined in a manner of determining whether the similarity result satisfies the object similarity condition through multiple rounds of cycles, based on this, a manner of generating an LOD resource with the lowest face number of the LOD resource and without affecting the visual effect is generated, the temporary LOD resource in this round and the temporary LOD resource in the previous round may also be determined, and the LOD resource with the optimal performance is determined when it is determined that the similarity satisfies the object similarity threshold; the specific implementation is as follows.

taking the candidate object as the initial object when the similarity result does not meet the object similarity condition;

adjusting the parameter adjustment ratio based on a preset ratio adjustment rule to obtain an adjusted parameter adjustment ratio;

Specifically, after determining the similarity result between the initial object and the candidate object, in the case where it is determined that the similarity result does not satisfy the object similarity condition, the candidate object can be taken as the initial object; and meanwhile, adjusting the parameter adjustment ratio based on a preset ratio adjustment rule to obtain the adjusted parameter adjustment ratio. And then, continuing to execute the step of adjusting the object parameters of the initial object by the adjusted parameter adjustment ratio to obtain the candidate object after parameter adjustment until the similarity result of the initial object and the candidate object meets the object similarity condition.

Following the above example, after determining the similarity between the original model and the temporary LOD resource, in the case where the similarity is greater than the object similarity threshold, the temporary LOD resource is taken as the model that needs to perform the face reduction operation, and the face reduction ratio is increased by 1%. Or, in the case that the similarity is smaller than the object similarity threshold, the temporary LOD resource is taken as a model which needs to execute the face reduction operation, and the face reduction ratio is reduced by 1%. And then, using a face reduction tool (Simplygon tool), carrying out face reduction on the model needing face reduction operation based on the adjusted face reduction ratio to obtain a new temporary LOD resource, continuing to perform operation of similarity between the model needing face reduction operation and the new temporary LOD resource until the similarity is equal to an object similarity threshold, determining to find an optimal face reduction ratio, and using a resource generated by using the face reduction ratio as the LOD resource.

It should be noted that a model has LOD resources with different finenesses in the case of different model screen occupation ratios (i.e., different distances from the camera), and therefore, each model screen occupation ratio has a different optimal reduction ratio. In addition, because the models are different from one another in the game, the optimal face reduction ratio of each model in the same model screen ratio may be the same or different. The object processing method provided by the description can determine the corresponding optimal area reduction ratio for different models under the condition of different model screen occupation ratios in an automatic mode, and generate the LOD resource with the optimal performance of the models under the different model screen occupation ratios based on the optimal area reduction ratio, so that the workload of art workers is reduced, and the game development cost is further reduced.

In addition, in practical applications, the object similarity threshold may be set to be plural. Based on this, under the condition that the similarity between the initial object and the candidate object is equal to the object similarity threshold, the target object has a plurality of object similarity thresholds, so that the purpose of automatically generating a plurality of LOD resources for each resource (game object or game role) is achieved, the LOD resources of different levels are rapidly obtained, the workload of art workers is reduced, and the cost increase of game development is avoided.

The following description further describes the object processing method with reference to fig. 2 by taking an application of the object processing method provided in the present application in a scene of automatically generating multi-detail-level resources as an example. Fig. 2 shows a processing flow chart of an object processing method applied in a scene of automatically generating multiple detail levels of resources according to an embodiment of the present application, which specifically includes the following steps:

step S202: and selecting a model needing the face reduction, and configuring the LOD model screen occupation ratio and the similarity limit.

The similarity limit may be understood as an object similarity threshold in the above embodiments.

Specifically, the object processing method provided by the present specification is capable of receiving a face reduction instruction for a model requiring face reduction, and determining the model requiring face reduction carried in the face reduction instruction. Or selecting a model needing surface reduction from a preset model library based on the surface reduction instruction, wherein the preset model library stores high-precision game models made by art personnel.

Also, it is also possible to receive a setting instruction for the similarity limit, and set the similarity limit to 90% in response to the setting instruction. And receiving a setting instruction for the screen occupancy, and setting the screen occupancy of the LOD model to 30% in response to the setting instruction.

Step S204: and subtracting the face of the original model by using a face subtraction tool to generate a temporary LOD resource.

Wherein the face reducing tool may be a Simplygon tool.

Specifically, using a Simplygon tool, the face reduction operation is performed on the model needing face reduction based on the initial face reduction ratio, and a temporary LOD resource is generated.

Step S206: setting the temporary LOD resource and the original resource as the same screen occupation ratio; and the original model and the temporary LOD resource are photographed in multiple directions to generate pictures.

Specifically, the temporary LOD resource and the original resource (model requiring face subtraction) are simultaneously set to a screen occupation ratio of 30%. And the two resources are photographed from each direction (such as front, back, left, right, upper and lower) to generate corresponding pictures.

Step S208: and comparing the generated pictures pixel by pixel, and calculating similarity.

Specifically, pictures generated by two resources in each direction are determined, and the difference of each opaque pixel in the pictures generated by the two resources under the same visual angle is compared, so that the similarity between the temporary LOD resource and the original resource is calculated.

Step S210: in the case where the similarity is equal to the similarity limit, the LOD resource is acquired.

Specifically, if similarity is limit, it is determined that an optimal reduction face ratio is found, and the resource is generated as the LOD resource using the optimal reduction face ratio.

Further, if similarity > limit (e.g., similarity greater than 90%), the reduction face ratio is increased and step S202 is performed; alternatively, if similarity < limit (e.g., similarity less than 90%), the reduction ratio is decreased. And performs step S202.

The object processing method provided by the specification is a scheme for automatically generating multi-detail-level resources, and the scheme is equivalent to providing a tool for automatically generating an LOD. The similarity between the LOD resources and the original resources can be compared automatically, and the LOD resources which have the least number of faces and meet the similarity requirement can be generated in batches automatically. The work load of fine arts has greatly been reduced, can guarantee simultaneously that the LOD resource effect that generates is optimal, only needs configuration LOD screen to account for than moreover, just can automize and generate this screen account for than the LOD resource that corresponds. Compared with the manual production of LOD resources, the tool has the advantages of high generation speed, low cost and excellent effect, and can be used for mass production of LOD resources.

Corresponding to the above method embodiment, the present application further provides an embodiment of an object processing apparatus, and fig. 3 shows a schematic structural diagram of an object processing apparatus provided in an embodiment of the present application. As shown in fig. 3, the apparatus includes:

an adjusting module 302 configured to adjust an object parameter of the initial object by a parameter adjustment ratio based on the object acquisition request, so as to obtain a candidate object after parameter adjustment;

a result determination module 304 configured to determine a similar result of the initial object to the candidate object;

an object determination module 306 configured to determine the candidate object as the target object if the similarity result satisfies an object similarity condition.

Optionally, the object processing apparatus further comprises a first ratio adjusting module configured to:

Optionally, the object processing apparatus further comprises a second ratio adjustment module configured to:

Optionally, the object determining module 306 is further configured to:

Optionally, the object determination module 306 is further configured to:

Optionally, the adjusting module 302 is further configured to:

determining a parameter adjustment ratio corresponding to the initial object;

Optionally, the result determining module 304 is further configured to:

acquiring at least two first images of the initial object and acquiring at least two second images of the candidate object based on at least two image acquisition perspectives;

acquiring visual angles based on the at least two images, and establishing an incidence relation between each first image and each second image;

determining a similarity result of the initial object and the candidate object based on the each first image, the each second image and the association relation.

Optionally, the result determining module 304 is further configured to:

Optionally, the object processing apparatus further comprises a presentation ratio adjusting module configured to:

determining an object display ratio corresponding to the target object;

The object processing device provided by the specification automatically adjusts an initial object based on a parameter adjustment ratio to obtain a candidate object under the condition that an object acquisition request for a target object is received, and determines the candidate object as the target object under the condition that the similarity result of the initial object and the candidate object meets an object similarity condition, so that the aim of automatically generating the target object is fulfilled, the problem that the workload of art workers is increased greatly due to the fact that models with different definitions need to be manufactured by the art workers is solved, the workload of the art workers is reduced, and the cost of game development is further reduced.

The above is a schematic configuration of an object processing apparatus of the present embodiment. It should be noted that the technical solution of the object processing apparatus and the technical solution of the object processing method belong to the same concept, and for details that are not described in detail in the technical solution of the object processing apparatus, reference may be made to the description of the technical solution of the object processing method. Further, the components in the device embodiment should be understood as functional blocks that must be created to implement the steps of the program flow or the steps of the method, and each functional block is not actually divided or separately defined. The device claims defined by such a set of functional modules are to be understood as a functional module framework for implementing the solution mainly by means of a computer program as described in the specification, and not as a physical device for implementing the solution mainly by means of hardware.

FIG. 4 illustrates a block diagram of a computing device 400 provided in accordance with one embodiment of the present description. The components of the computing device 400 include, but are not limited to, a memory 410 and a processor 420. Processor 420 is coupled to memory 410 via bus 430 and database 450 is used to store data.

Computing device 400 also includes access device 440, access device 440 enabling computing device 400 to communicate via one or more networks 460. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 440 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.

In one embodiment of the present description, the above-described components of computing device 400, as well as other components not shown in FIG. 4, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device structure shown in FIG. 4 is for purposes of example only and is not limiting as to the scope of the description. Those skilled in the art may add or replace other components as desired.

Computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 400 may also be a mobile or stationary server.

Wherein the processor 420 is configured to execute the computer-executable instructions of the object processing method.

The foregoing is a schematic diagram of a computing device of the present embodiment. It should be noted that the technical solution of the computing device belongs to the same concept as the technical solution of the object processing method, and for details that are not described in detail in the technical solution of the computing device, reference may be made to the description of the technical solution of the object processing method.

An embodiment of the present application also provides a computer-readable storage medium storing computer instructions, which when executed by a processor, are used for an object processing method.

The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the object processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the object processing method.

An embodiment of the present application further provides a chip, which stores a computer program, and when the computer program is executed by the chip, the steps of the object processing method are implemented.

The foregoing description of specific embodiments of the present application has been presented. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.

It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

The preferred embodiments of the present application disclosed above are intended only to aid in the explanation of the application. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the application and its practical applications, to thereby enable others skilled in the art to best understand and utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. An object processing method, comprising:

determining a similarity result of the initial object and the candidate object;

and determining the candidate object as the target object under the condition that the similarity result meets the object similarity condition.

2. The object processing method according to claim 1, wherein after determining the similarity between the initial object and the candidate object, the method further comprises:

3. The object processing method according to claim 1, wherein after determining the similarity between the initial object and the candidate object, the method further comprises:

4. The object processing method according to claim 1, wherein the determining the candidate object as the target object if the similarity result satisfies an object similarity condition comprises:

5. The object processing method according to claim 1, wherein the determining the candidate object as the target object if the similarity result satisfies an object similarity condition comprises:

6. The object processing method according to claim 1, wherein the obtaining the parameter-adjusted candidate object by adjusting the object parameter of the initial object by the parameter adjustment ratio based on the object acquisition request comprises:

determining a parameter adjustment ratio corresponding to the initial object;

7. The object processing method of claim 1, wherein the determining the similarity between the initial object and the candidate object comprises:

determining a similarity result of the initial object and the candidate object based on the each first image, the each second image and the association relationship.

8. The object processing method according to claim 7, wherein the establishing an association relationship between each first image and each second image based on the at least two image acquisition perspectives comprises:

9. The object processing method according to claim 7, wherein the determining a similarity result between the initial object and the candidate object based on the each first image, the each second image and the association relationship comprises:

10. The object processing method of claim 9, wherein determining the image similarity between each first image and the associated second image based on the pixel information of each pixel in each first image and the pixel information of each pixel in the associated second image comprises:

11. The object processing method of claim 1, wherein before determining the similarity between the initial object and the candidate object, further comprising:

determining an object display ratio corresponding to the target object;

12. An object processing apparatus, comprising:

13. A computing device, comprising:

a memory and a processor;

the memory is configured to store computer-executable instructions, and the processor is configured to execute the computer-executable instructions to implement the steps of the object processing method according to any one of claims 1 to 11.

14. A computer-readable storage medium storing computer instructions, which when executed by a processor, implement the steps of the object processing method of any one of claims 1 to 11.