CN117414578A - Game resource distribution system and method based on cloud computing - Google Patents
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/50—Controlling the output signals based on the game progress
- A63F13/52—Controlling the output signals based on the game progress involving aspects of the displayed game scene
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/55—Controlling game characters or game objects based on the game progress
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/70—Game security or game management aspects
- A63F13/77—Game security or game management aspects involving data related to game devices or game servers, e.g. configuration data, software version or amount of memory
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
- A63F2300/53—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers details of basic data processing
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Abstract
A game resource distribution system and method based on cloud computing relates to a game resource distribution system and method. The invention aims to solve the problem that the efficiency of constructing the game scene is poor so as to greatly influence the game experience of a player because more game resources are needed for constructing the game scene and the loading or switching can be successful only after a long time is needed. The system comprises a virtual object control module, a resource identification acquisition module, a resource identification pressing-in module, a game resource loading module, a target scene construction module, an image processing module, at least one processor and a memory. The invention belongs to the technical field of online games.
Description
Technical Field
The invention relates to a game resource distribution system and a method, belonging to the technical field of online games.
Background
Along with the development of terminal equipment and game industry, a large number of games with different themes are played so as to meet the requirements of players; in some games, a large number of game resources, such as model resources, poster resources, material resources, etc., are required to be utilized to construct a game scene, and the game resources can enrich game details, thereby bringing an excellent game experience to players. Along with the progress of game content, new game scenes are required to be loaded continuously or the game scenes are required to be switched, and at the moment, related game resources of the game scenes are required to be acquired from a disk of the terminal equipment; however, since a lot of game resources are required for constructing the game scene, it takes a long time to load or switch successfully, and the efficiency of constructing the game scene is poor, thereby greatly affecting the game experience of the player.
Disclosure of Invention
The invention aims to solve the problem that the efficiency of constructing a game scene is poor so as to greatly influence the game experience of a player because more game resources are needed for constructing the game scene, and the loading or switching can be successful only after a long time is needed, and further provides a game resource distribution system and a game resource distribution method based on cloud computing.
The technical scheme adopted by the invention for solving the problems is as follows: the system comprises a virtual object control module, a resource identification acquisition module, a resource identification pressing-in module, a game resource loading module, a target scene construction module, an image processing module, at least one processor and a memory;
the virtual object control module is used for controlling the game virtual object to execute game actions in a game sub-scene in the game process, wherein the game scene comprises a plurality of game sub-scenes;
the resource identification acquisition module is used for determining a target game sub-scene to be switched by the game virtual object and acquiring a plurality of game resource identifications corresponding to the target game sub-scene, wherein the game resource identifications are used for indicating game resources corresponding to the game resource identifications;
the game identifier pressing-in module is used for distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread and pressing the game resource identifiers into storage areas corresponding to the threads;
the game resource loading module is used for sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate, and loading a plurality of game resources corresponding to the game resource identifiers into the memory according to the ejected game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
the target scene construction module is used for acquiring a plurality of game resources from the memory when the game virtual object switches game scenes, and constructing a target game sub-scene according to the plurality of game resources;
the image processing module is used for carrying out noise reduction processing on the game image when the game scene is switched, and carrying out correction processing on distortion generated by the image when the converted game scene image is distorted;
the memory is configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to allocate game resources.
The method comprises the following steps:
step 1, in the game progress process, controlling a game virtual object to execute game actions in a game sub-scene; wherein the game scene comprises a plurality of game sub-scenes;
step 2, determining a target game sub-scene to be switched by the game virtual object, and acquiring a plurality of game resource identifiers corresponding to the target game sub-scene; the game resource identifier is used for indicating a game resource corresponding to the game resource identifier;
step 3, distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread, and pressing the game resource identifiers into storage areas corresponding to the threads;
step 4, sequentially popping up a plurality of game resource identifiers from the storage area according to the pop-up rate, and loading a plurality of game resources corresponding to the game resource identifiers into a memory according to the popped-up game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
step 5, when the game virtual object switches game scenes, a plurality of game resources are obtained from the memory, and a target game sub-scene is constructed according to the game resources;
and 6, after the game virtual object switches the game scene, performing noise reduction processing on the images in the switched game scene, and performing correction processing on the distorted images in the game scene.
Further, the target game sub-scene is a game scene within a preset range of a position to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring a position to be switched of the game virtual object, and determining a game sub-scene where the position is located; determining the game sub-scene as a target game sub-scene to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring control operation aiming at the game virtual object, and determining a target game sub-scene to be switched by the game virtual object according to the control operation;
obtaining a game scene corresponding to a game, and dividing the game scene into a plurality of game sub-scenes; wherein each game sub-scene comprises a plurality of game resources; and acquiring a plurality of game resource identifiers corresponding to the game sub-scene according to the plurality of game resources in the game sub-scene.
Further, the allocating the plurality of game resource identifiers of the target game sub-scene to at least one thread, and pressing the plurality of game resource identifiers into the storage areas corresponding to the threads includes:
distributing a plurality of game resource identifiers of the target game sub-scene to at least one sub-thread through a main thread, and pressing the game resource identifiers into storage areas corresponding to the sub-threads;
the step of sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate comprises the following steps:
adjusting the ejection rate, and sequentially ejecting a plurality of game resource identifiers from the storage area according to the adjusted ejection rate;
adjusting the frequency of sequentially ejecting the game resource identifiers from the storage area and/or adjusting the number of sequentially ejecting the game resource identifiers from the storage area so as to adjust the ejection rate;
the ejection rate comprises 0, and when the ejection rate is 0, stopping ejecting the game resource identification from the storage area;
the adjusting the pop-up rate includes:
when the thread creates the game resource corresponding to the game sub-scene, the pop-up rate is adjusted to 0 to stop
And ejecting the game resource identifiers from the storage area, or reducing the ejection rate to reduce the rate of sequentially ejecting a plurality of game resource identifiers from the storage area.
Further, the step of performing noise reduction processing on the game image in the step 6 includes:
step one, inputting an image X with noise;
step two, super-pixel segmentation is carried out on the image X through an SLIC method, and pixels similar to each other in the image are combinedForming a superpixel set { R } 1 ,,......,R N }；
Step three, carrying out self-adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters;
step four, gathering each super pixel to obtain a final noise reduction image X out ；
Step five, outputting a noise reduction image X out 。
Further, in the third step, the step of performing adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters includes:
step 1, when d (x j ,x k ) Clustering and normalizing to obtain clusters when the noise level is smaller than or equal to the threshold value related to the noise leveld(x j ,x k ) As a similarity measure, is the euclidean distance:
in the above-mentioned formula(s),is an image block centered on a pixel position k, d (x j ,x k ) The smaller the distance of (a) represents the image block x j And x k The more similar;
step 2, denoising each cluster by using PCA;
step 3, combining the clustering to obtain the noise reduction super-image
Further, in step 2, PCA is used to denoise each cluster:
step (1), PCA transformation is carried out;
step (2), hard threshold dimension selection: removing singular values less thanTo obtain X r ＝U r P r ；
Step (3), for each selected dimension: estimating a filter parameter h by using a local polynomial approximation;
step (4), for each selected dimension: performing sub-optimal wiener filtering treatment to obtain
And (5) converting the inverse PCA.
Further, the step of correcting the distorted image in the game scene in the step 6 includes:
step one, a three-dimensional vibration distortion correction model is established;
scanning to obtain an ideal sampling point set;
fitting the sampling point positions by a least square method;
and step four, correcting all sampling grid point data to finally obtain corrected three-dimensional morphology.
Further, for an ideal scan point set in step (one):
P＝{P i |(x i ,y i ,z i ,I i ),i∈[1,N]}，
the acceleration sampling point set is as follows:
A＝{A i |(a xi ,a yi ,a zi ),i∈[1,N]}，
the vibration displacement is as follows:
O＝G(A)＝∫∫A(a xi ,a yi ,a zi )dt 2 ，
the set of deflection data caused by vibration is:
O＝{O i |(Δx i ,Δy i ,Δz i ),i∈[1,N]}，
through correction, the actual sampling point set is:
P′＝{P i ′|(x i +Δx i ,y i +Δy i ,z i +Δz i ,I i ),i∈[1,N]}。
further, in the step (three), the sampling point position fitted by the least square method is used as the three-dimensional reconstructed XY lattice point position:
the corresponding Z-direction coordinate and light intensity set are as follows:
P(x′ i ,y′ i )＝{P j (x′ i ,y′ i )|(z j +Δz j ,I j ),j∈[1,N]}，
set of pairs P (x' i ,y′ i ) The actual Z-direction height is obtained by reconstruction from the centroid method.
The beneficial effects of the invention are as follows: 1. the invention can control the game virtual object to execute the game action in the game sub-scene in the game progress process, determine the target game sub-scene to be switched by the game virtual object, acquire a plurality of game resource identifications corresponding to the target game sub-scene, allocate the plurality of game resource identifications of the target game sub-scene to at least one thread, press the plurality of game resource identifications into a storage area corresponding to the thread, sequentially pop up the plurality of game resource identifications from the storage area according to the pop-up rate, load the plurality of game resources corresponding to the plurality of game resource identifications into the memory according to the popped plurality of game resource identifications, acquire the plurality of game resources from the memory when the game virtual object switches the game scene, and construct the target game sub-scene according to the plurality of game resources;
2. according to the scheme, on one hand, the target game sub-scene to be switched can be determined, and the loading range of game resources is reduced, so that the construction efficiency of the game scene is improved; on the other hand, game resources of the target game sub-scene can be loaded into the memory, and when the game scene is required to be built according to the game resources, the game resources are directly obtained from the memory, so that the problem of low speed of obtaining the game resources from a disk is avoided, and the building efficiency of the game scene is improved;
3. the method and the device can control the pop-up rate of the game resource identification, thereby controlling the loading rate of the game resource to the memory, avoiding the process of loading a plurality of game resources of the target game sub-scene from influencing the construction of the current game sub-scene, ensuring the stability of the current game picture and further ensuring the game experience of players;
4. according to the invention, super-pixel segmentation is carried out on the image by an SLIC method, so that the calculation complexity is reduced; collecting similar image blocks through self-adaptive clustering of noise level related parameters, so that good capability of retaining image detail structures is obtained; removing noise dominant dimensions through hard threshold dimension selection based on characteristic values, and reserving signal dominant dimensions; obtaining better noise reduction effect by utilizing intra-dimensional suboptimal wiener filtering;
5. the noise-reduced image of the algorithm provided by the invention has a signal-to-noise ratio improvement factor of 13.47 compared with the noise-containing image, and the invention has good performance on MSE, PSNR, SSIM and FSIM, and is superior to NLM algorithm, KSVD algorithm and LPG-PCA algorithm; the invention can keep the detail information of the image while having good noise reduction performance, and provides high signal-to-noise ratio image for image enhancement;
6. the three-dimensional distortion correction method of the image adopted by the invention provides a method for correcting the position of an actual sampling coordinate point to realize the restoration of the three-dimensional shape; firstly, analyzing a three-dimensional imaging process, and pointing out that the main reason of three-dimensional morphology distortion caused by vibration is axial vibration by combining a centroid method for realizing morphology reconstruction; by acquiring 1 μm and 5 μm step data and calculating the standard deviation of the reference point sequence, the correction effect is remarkable from 0.1836 μm to 0.0536 μm before correction.
Drawings
FIG. 1 is a block flow diagram of the method of the present invention;
FIG. 2 is a schematic diagram of a plurality of corresponding game sub-scenes scanned to obtain resource distribution data in the method of the present invention;
FIG. 3 is a schematic diagram of image denoising in accordance with the method of the present invention;
fig. 4 is a schematic diagram of a sampling envelope after three-dimensional distortion correction of an image in the method of the present invention.
Detailed Description
The first embodiment is as follows: referring to fig. 1 and fig. 2, a game resource allocation system based on cloud computing according to this embodiment includes a virtual object control module, a resource identifier acquisition module, a resource identifier push module, a game resource loading module, a target scene construction module, an image processing module, at least one processor, and a memory;
the virtual object control module is used for controlling the game virtual object to execute game actions in a game sub-scene in the game process, wherein the game scene comprises a plurality of game sub-scenes;
the resource identification acquisition module is used for determining a target game sub-scene to be switched by the game virtual object and acquiring a plurality of game resource identifications corresponding to the target game sub-scene, wherein the game resource identifications are used for indicating game resources corresponding to the game resource identifications;
the game identifier pressing-in module is used for distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread and pressing the game resource identifiers into storage areas corresponding to the threads;
the game resource loading module is used for sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate, and loading a plurality of game resources corresponding to the game resource identifiers into the memory according to the ejected game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
the target scene construction module is used for acquiring a plurality of game resources from the memory when the game virtual object switches game scenes, and constructing a target game sub-scene according to the plurality of game resources;
the image processing module is used for carrying out noise reduction processing on the game image when the game scene is switched, and carrying out correction processing on distortion generated by the image when the converted game scene image is distorted;
the memory is configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to allocate game resources.
The second embodiment is as follows: referring to fig. 1 and 2, the steps of a game resource allocation method based on cloud computing according to the present embodiment include:
step 1, in the game progress process, controlling a game virtual object to execute game actions in a game sub-scene; wherein the game scene comprises a plurality of game sub-scenes;
step 2, determining a target game sub-scene to be switched by the game virtual object, and acquiring a plurality of game resource identifiers corresponding to the target game sub-scene; the game resource identifier is used for indicating a game resource corresponding to the game resource identifier;
step 3, distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread, and pressing the game resource identifiers into storage areas corresponding to the threads;
step 4, sequentially popping up a plurality of game resource identifiers from the storage area according to the pop-up rate, and loading a plurality of game resources corresponding to the game resource identifiers into a memory according to the popped-up game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
step 5, when the game virtual object switches game scenes, a plurality of game resources are obtained from the memory, and a target game sub-scene is constructed according to the game resources;
and 6, after the game virtual object switches the game scene, performing noise reduction processing on the images in the switched game scene, and performing correction processing on the distorted images in the game scene.
And a third specific embodiment: referring to fig. 1 and fig. 2, a description is given of the present embodiment, where the target game sub-scene of the cloud computing-based game resource allocation method is a game scene within a preset range of a position to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring a position to be switched of the game virtual object, and determining a game sub-scene where the position is located; determining the game sub-scene as a target game sub-scene to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring control operation aiming at the game virtual object, and determining a target game sub-scene to be switched by the game virtual object according to the control operation;
obtaining a game scene corresponding to a game, and dividing the game scene into a plurality of game sub-scenes; wherein each game sub-scene comprises a plurality of game resources; and acquiring a plurality of game resource identifiers corresponding to the game sub-scene according to the plurality of game resources in the game sub-scene.
The specific embodiment IV is as follows: referring to fig. 1 and 2, the method for allocating a plurality of game resource identifiers of the target game sub-scene to at least one thread and pressing a plurality of game resource identifiers into memory areas corresponding to the threads according to the method for allocating game resources based on cloud computing in this embodiment is described, and includes:
distributing a plurality of game resource identifiers of the target game sub-scene to at least one sub-thread through a main thread, and pressing the game resource identifiers into storage areas corresponding to the sub-threads;
the step of sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate comprises the following steps:
adjusting the ejection rate, and sequentially ejecting a plurality of game resource identifiers from the storage area according to the adjusted ejection rate;
adjusting the frequency of sequentially ejecting the game resource identifiers from the storage area and/or adjusting the number of sequentially ejecting the game resource identifiers from the storage area so as to adjust the ejection rate;
the ejection rate comprises 0, and when the ejection rate is 0, stopping ejecting the game resource identification from the storage area;
the adjusting the pop-up rate includes:
when the thread creates the game resource corresponding to the game sub-scene, the pop-up rate is adjusted to 0 to stop
And ejecting the game resource identifiers from the storage area, or reducing the ejection rate to reduce the rate of sequentially ejecting a plurality of game resource identifiers from the storage area.
Fifth embodiment: referring to fig. 3, a step of performing noise reduction processing on a game image in step 6 of the game resource allocation method based on cloud computing according to the present embodiment includes:
step one, inputting an image X with noise;
step two, performing superpixel segmentation on the image X by an SLIC method, and combining pixels similar to each other in the image to form a superpixel set { R } 1 ,,......,R N }；
Step three, carrying out self-adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters;
step four, gathering each super pixel to obtain a final noise reduction image X out ；
Step five, outputting a noise reduction image X out 。
Specific embodiment six: referring to fig. 3, a step of performing adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters in the third step of the game resource allocation method based on cloud computing according to the present embodiment includes:
step 1, when d (x j ,x k ) Clustering and normalizing to obtain clusters when the noise level is smaller than or equal to the threshold value related to the noise leveld(x j ,x k ) As a similarity measure, is the euclidean distance:
in the above-mentioned formula(s),is an image block centered on a pixel position k, d (x j ,x k ) The smaller the distance of (a) represents the image block x j And x k The more similar;
step 2, denoising each cluster by using PCA;
step 3, combining the clustering to obtain the noise reduction super-image
Seventh embodiment: referring to fig. 3, in the description of the present embodiment, in step 2 of the cloud computing-based game resource allocation method according to the present embodiment, PCA is used to denoise each cluster:
step (1), PCA transformation is carried out;
step (2), hard threshold dimension selection: removing singular values less thanTo obtain X r ＝U r P r ；
Step (3), for each selected dimension: estimating a filter parameter h by using a local polynomial approximation;
step (4), for each selected dimension: performing sub-optimal wiener filtering treatment to obtain
And (5) converting the inverse PCA.
Eighth embodiment: referring to fig. 4, a step of correcting a distorted image in a game scene in step 6 of the game resource allocation method based on cloud computing according to the present embodiment includes:
step one, a three-dimensional vibration distortion correction model is established;
scanning to obtain an ideal sampling point set;
fitting the sampling point positions by a least square method;
and step four, correcting all sampling grid point data to finally obtain corrected three-dimensional morphology.
Detailed description nine: referring to fig. 4, in the step (a) of the game resource allocation method based on cloud computing according to the present embodiment, an ideal scan point set is described:
P＝{P i |(x i ,y i ,z i ,I i ),i∈[1,N]}，
the acceleration sampling point set is as follows:
A＝{A i |(a xi ,a yi ,a zi ),i∈[1,N]}，
the vibration displacement is as follows:
O＝G(A)＝∫∫A(a xi ,a yi ,a zi )dt 2 ，
the set of deflection data caused by vibration is:
O＝{O i |(Δx i ,Δy i ,Δz i ),i∈[1,N]}，
through correction, the actual sampling point set is:
P′＝{P i ′|(x i +Δx i ,y i +Δy i ,z i +Δz i ,I i ),i∈[1,N]}。
detailed description ten: referring to fig. 4, in the step (iii) of the game resource allocation method based on cloud computing according to the present embodiment, the sampling point position fitted by the least square method is used as the XY grid point position of the three-dimensional reconstruction:
the corresponding Z-direction coordinate and light intensity set are as follows:
P(x′ i ,y′ i )＝{P j (x′ i ,y′ i )|(z j +Δz j ,I j ),j∈[1,N]}，
set of pairs P (x' i ,y′ i ) The actual Z-direction height is obtained by reconstruction from the centroid method.
The present invention is not limited to the preferred embodiments, but is capable of modification and variation in detail, and other embodiments, such as those described above, of making various modifications and equivalents will fall within the spirit and scope of the present invention.
Claims (10)
1. The game resource distribution system based on cloud computing is characterized in that: the game resource distribution system based on cloud computing comprises a virtual object control module, a resource identification acquisition module, a resource identification pressing-in module, a game resource loading module, a target scene construction module, an image processing module, at least one processor and a memory;
the virtual object control module is used for controlling the game virtual object to execute game actions in a game sub-scene in the game process, wherein the game scene comprises a plurality of game sub-scenes;
the resource identification acquisition module is used for determining a target game sub-scene to be switched by the game virtual object and acquiring a plurality of game resource identifications corresponding to the target game sub-scene, wherein the game resource identifications are used for indicating game resources corresponding to the game resource identifications;
the game identifier pressing-in module is used for distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread and pressing the game resource identifiers into storage areas corresponding to the threads;
the game resource loading module is used for sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate, and loading a plurality of game resources corresponding to the game resource identifiers into the memory according to the ejected game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
the target scene construction module is used for acquiring a plurality of game resources from the memory when the game virtual object switches game scenes, and constructing a target game sub-scene according to the plurality of game resources;
the image processing module is used for carrying out noise reduction processing on the game image when the game scene is switched, and carrying out correction processing on distortion generated by the image when the converted game scene image is distorted;
the memory is configured to store one or more programs that, when executed by the one or more processors, cause the one or more processors to allocate game resources.
2. A game resource allocation method based on cloud computing is characterized by comprising the following steps: the game resource allocation method based on cloud computing comprises the following steps:
step 1, in the game progress process, controlling a game virtual object to execute game actions in a game sub-scene; wherein the game scene comprises a plurality of game sub-scenes;
step 2, determining a target game sub-scene to be switched by the game virtual object, and acquiring a plurality of game resource identifiers corresponding to the target game sub-scene; the game resource identifier is used for indicating a game resource corresponding to the game resource identifier;
step 3, distributing a plurality of game resource identifiers of the target game sub-scene to at least one thread, and pressing the game resource identifiers into storage areas corresponding to the threads;
step 4, sequentially popping up a plurality of game resource identifiers from the storage area according to the pop-up rate, and loading a plurality of game resources corresponding to the game resource identifiers into a memory according to the popped-up game resource identifiers; the pop-up rate is used for indicating the rate of sequentially popping up the game resource identifiers from the storage area;
step 5, when the game virtual object switches game scenes, a plurality of game resources are obtained from the memory, and a target game sub-scene is constructed according to the game resources;
and 6, after the game virtual object switches the game scene, performing noise reduction processing on the images in the switched game scene, and performing correction processing on the distorted images in the game scene.
3. The cloud computing-based game resource allocation method according to claim 2, wherein: the target game sub-scene is a game scene within a preset range of a position to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring a position to be switched of the game virtual object, and determining a game sub-scene where the position is located; determining the game sub-scene as a target game sub-scene to be switched by the game virtual object;
the determining the target game sub-scene to be switched by the game virtual object comprises the following steps: acquiring control operation aiming at the game virtual object, and determining a target game sub-scene to be switched by the game virtual object according to the control operation;
obtaining a game scene corresponding to a game, and dividing the game scene into a plurality of game sub-scenes; wherein each game sub-scene comprises a plurality of game resources; and acquiring a plurality of game resource identifiers corresponding to the game sub-scene according to the plurality of game resources in the game sub-scene.
4. The cloud computing-based game resource allocation method according to claim 2, wherein: the allocating the plurality of game resource identifiers of the target game sub-scene to at least one thread, and pressing the plurality of game resource identifiers into the storage areas corresponding to the threads includes:
distributing a plurality of game resource identifiers of the target game sub-scene to at least one sub-thread through a main thread, and pressing the game resource identifiers into storage areas corresponding to the sub-threads;
the step of sequentially ejecting a plurality of game resource identifiers from the storage area according to the ejection rate comprises the following steps:
adjusting the ejection rate, and sequentially ejecting a plurality of game resource identifiers from the storage area according to the adjusted ejection rate;
adjusting the frequency of sequentially ejecting the game resource identifiers from the storage area and/or adjusting the number of sequentially ejecting the game resource identifiers from the storage area so as to adjust the ejection rate;
the ejection rate comprises 0, and when the ejection rate is 0, stopping ejecting the game resource identification from the storage area;
the adjusting the pop-up rate includes:
and when the thread creates the game resource corresponding to the game sub-scene, adjusting the pop-up rate to 0 so as to stop popping up the game resource identification from the storage area, or reducing the pop-up rate so as to reduce the rate of sequentially popping up a plurality of game resource identifications from the storage area.
5. The cloud computing-based game resource allocation method according to claim 2, wherein: the step of performing noise reduction processing on the game image in the step 6 includes:
step one, inputting an image X with noise;
step two, performing superpixel segmentation on the image X by an SLIC method, and combining pixels similar to each other in the image to form a superpixel set { R } 1 ,,......,R N }；
Step three, carrying out self-adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters;
step four, gathering each super pixel to obtain a final noise reduction image X out ；
Step five, outputting a noise reduction image X out 。
6. The cloud computing-based game resource allocation method according to claim 5, wherein: in the third step, the step of performing adaptive clustering on similar image blocks in each super pixel to obtain similar block clusters comprises the following steps:
step 1, when d (x j ,x k ) Clustering and normalizing to obtain clusters when the noise level is smaller than or equal to the threshold value related to the noise leveld(x j ,x k ) As a similarity measure, is the euclidean distance:
in the above-mentioned formula(s),is an image block centered on a pixel position k, d (x j ,x k ) The smaller the distance of (a) represents the image block x j And x k The more similar;
step 2, denoising each cluster by using PCA;
step 3, combining the clustering to obtain the noise reduction super-image
7. The cloud computing-based game resource allocation method according to claim 6, wherein: denoising each cluster using PCA in step 2:
step (1), PCA transformation is carried out;
step (2), hard threshold dimension selection: removing singular values less thanTo obtain X r ＝U r P r ；
Step (3), for each selected dimension: estimating a filter parameter h by using a local polynomial approximation;
step (4), for each selected dimension: performing sub-optimal wiener filtering treatment to obtain
And (5) converting the inverse PCA.
8. The cloud computing-based game resource allocation method according to claim 2, wherein: the step 6 of correcting the distorted image in the game scene comprises the following steps:
step one, a three-dimensional vibration distortion correction model is established;
scanning to obtain an ideal sampling point set;
fitting the sampling point positions by a least square method;
and step four, correcting all sampling grid point data to finally obtain corrected three-dimensional morphology.
9. The cloud computing-based game resource allocation method according to claim 8, wherein: for an ideal set of scan points in step (one):
P＝{P i |(x i ,y i ,z i ,I i ),i∈[1,N]}，
the acceleration sampling point set is as follows:
A＝{A i |(a xi ,a yi ,a zi ),i∈[1,N]}，
the vibration displacement is as follows:
O＝G(A)＝∫∫A(a xi ,a yi ,a zi )dt 2 ，
the set of deflection data caused by vibration is:
O＝{O i |(Δx i ,Δy i ,Δz i ),i∈[1,N]}，
through correction, the actual sampling point set is:
P′＝{P i ′|(x i +Δx i ,y i +Δy i ,z i +Δz i ,I i ),i∈[1,N]}。
10. the cloud computing-based game resource allocation method according to claim 8, wherein: in the step (III), the sampling point position fitted by the least square method is used as the XY lattice point position of the three-dimensional reconstruction:
the corresponding Z-direction coordinate and light intensity set are as follows:
P(x′ i ,y′ i )＝{P j (x′ i ,y′ i )|(z j +Δz j ,I j ),j∈[1,N]}，
set of pairs P (x' i ,y′ i ) The actual Z-direction height is obtained by reconstruction from the centroid method.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109712153A (en) * | 2018-12-25 | 2019-05-03 | 杭州世平信息科技有限公司 | A kind of remote sensing images city superpixel segmentation method |
| WO2022121842A1 (en) * | 2020-12-09 | 2022-06-16 | 上海肇观电子科技有限公司 | Correction method and apparatus for text image, and device, and medium |
| CN115909025A (en) * | 2022-09-30 | 2023-04-04 | 北京空间飞行器总体设计部 | Terrain vision autonomous detection and identification method for small celestial body surface sampling point |
| CN116747514A (en) * | 2023-06-26 | 2023-09-15 | 网易（杭州）网络有限公司 | Game scene preloading method, game scene preloading device, medium and equipment |
-
2023
- 2023-10-19 CN CN202311361725.9A patent/CN117414578B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109712153A (en) * | 2018-12-25 | 2019-05-03 | 杭州世平信息科技有限公司 | A kind of remote sensing images city superpixel segmentation method |
| WO2022121842A1 (en) * | 2020-12-09 | 2022-06-16 | 上海肇观电子科技有限公司 | Correction method and apparatus for text image, and device, and medium |
| CN115909025A (en) * | 2022-09-30 | 2023-04-04 | 北京空间飞行器总体设计部 | Terrain vision autonomous detection and identification method for small celestial body surface sampling point |
| CN116747514A (en) * | 2023-06-26 | 2023-09-15 | 网易（杭州）网络有限公司 | Game scene preloading method, game scene preloading device, medium and equipment |
Non-Patent Citations (2)
| Title |
|---|
| 张小凤: "基于图像超像素分析的图像分割方法", 计算机技术与发展, vol. 28, no. 7, 31 July 2018 (2018-07-31), pages 25 - 28 * |
| 由小玉: "共焦显微测量三维畸变自校准方法研究", 中国博士学位论文全文数据库 信息科技辑, 1 December 2021 (2021-12-01), pages 7 - 108 * |
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