Game picture generation method and device, storage medium and electronic equipment
By acquiring vehicle environment information and predicting object states to generate dynamic game visuals, the problem of motion sickness caused by the conflict between the visual and inner ear balance systems in existing technologies is solved. It achieves synchronized perception of vision and inner ear, reduces motion sickness, and improves user experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-03
- Publication Date
- 2026-03-13
AI Technical Summary
Existing technologies that use sound alerts can only partially alleviate motion sickness in passengers and cannot effectively solve the problem of motion sickness caused by the conflict between the visual and inner ear balance systems.
By acquiring environmental information about the vehicle's driving status, predicting the state information of multiple objects, and generating dynamic game visuals of the target, users can perceive changes in the vehicle's driving status and alleviate motion sickness through visual stimulation.
By stimulating visual information and simultaneously sensing changes in vehicle status through the inner ear system, the system can reduce motion sickness and enhance the passenger experience.
Smart Images
Figure CN121648554A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of cloud gaming technology, and in particular to a method, apparatus, storage medium and electronic device for generating game screens. Background Technology
[0002] In a car environment, if passengers focus on static objects such as mobile phones or books, it can create a conflict between their visual and inner ear balance systems, causing them to feel motion sickness.
[0003] Currently, the main method is to play simulated sounds before the vehicle accelerates, thus alerting passengers to the impending acceleration and preparing them psychologically to reduce motion sickness.
[0004] However, using this method to help passengers alleviate motion sickness solely through sound reminders does not alleviate the conflict between the visual and inner ear balance systems, resulting in a poor effect on reducing motion sickness. Summary of the Invention
[0005] In view of this, this application provides a method, apparatus, storage medium and electronic device for generating game screens, with the main purpose of improving the existing technology that only helps passengers reduce motion sickness through sound reminders, but does not alleviate the technical problem that the effect of helping passengers reduce motion sickness is poor due to the conflict between the visual and inner ear balance systems.
[0006] Firstly, this application provides a method for generating game screens, including: Acquire environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin; Based on the environmental information, the state information of multiple objects in the vehicle's driving environment is predicted; In response to the presence of a target object among the plurality of objects that changes the driving state of the vehicle, the driving state change data of the vehicle is determined based on the state information of the target object. The game screen is updated to the target dynamic game screen corresponding to the generated driving state change data, and the target dynamic game screen is used by the user to perceive the changes in the vehicle's driving state.
[0007] Secondly, this application provides a device for generating game screens, comprising: The acquisition module is configured to acquire environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin; The prediction module is configured to predict the state information of multiple objects in the vehicle's driving environment based on the environmental information. The determination module is configured to determine the driving state change data of the vehicle based on the state information of the target object in response to the existence of a target object among the plurality of objects that changes the driving state of the vehicle. The generation module is configured to update the game screen to the target dynamic game screen corresponding to the generated driving state change data, the target dynamic game screen being used by the user to perceive the changes in the vehicle's driving state.
[0008] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the game screen generation method described in the first aspect.
[0009] Fourthly, this application provides an electronic device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the computer program to implement the game screen generation method described in the first aspect.
[0010] Fifthly, this application provides a computer program product, which includes a computer program that, when executed by a processor, implements the game screen generation method described in the first aspect.
[0011] By employing the above technical solutions, this application provides a method, apparatus, storage medium, and electronic device for generating game screens. Compared with existing technologies, this application acquires environmental information related to the vehicle's driving state and the user's game screen in the vehicle's cabin; predicts the state information of multiple objects in the vehicle's driving environment based on the environmental information; responds to the presence of a target object among the multiple objects that changes the vehicle's driving state, and determines the vehicle's driving state change data based on the target object's state information; updates the game screen to generate a target dynamic game screen corresponding to the driving state change data, and the target dynamic game screen is used by the user to perceive the vehicle's driving state change; thus, this application allows the user to perceive the vehicle's driving state change through the target game screen when the vehicle's driving state changes. Furthermore, when the user plays games while traveling, they can perceive the vehicle's driving state change based on the target game screen, allowing the user's visual and inner ear systems to perceive similar driving state changes, thereby helping to reduce motion sickness and improving the user experience. Attached Figure Description
[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0014] Figure 1 A flowchart illustrating a method for generating game screens according to an embodiment of this application is shown; Figure 2 A flowchart illustrating a method for generating game screens according to an embodiment of this application is shown; Figure 3 A schematic diagram of the structure of a game screen generation device provided in an embodiment of this application is shown; Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation
[0015] The embodiments of this application will now be described in more detail with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.
[0016] To address the problem that existing technologies, which only rely on sound alerts to alleviate motion sickness but fail to address the conflict between visual and inner ear balance systems, resulting in poor effectiveness in reducing motion sickness, this embodiment provides a method for generating game visuals, such as... Figure 1 As shown, the method includes: Step 101: Obtain environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin.
[0017] In this embodiment of the application, the vehicle can be a vehicle in which a user sits in the cabin. Correspondingly, the user in the cabin can be a user who plays cloud games while riding in the vehicle. Cloud gaming is a game operation and distribution mode based on cloud computing and streaming media technology. It transfers the core processes of game calculation and rendering from local devices (such as mobile phones, PCs, and TVs) to remote cloud servers. Users receive game screen video streams through the network and upload operation commands in real time, realizing a lightweight experience of instant play.
[0018] In some examples, environmental information related to the vehicle's driving status may include, but is not limited to, the vehicle's location information, weather information, information about people on the road, obstacle conditions, traffic information, and so on.
[0019] In this embodiment, the user's game screen in the vehicle cabin can be the game screen that the user is experiencing in the vehicle cabin; for example, if user 1 opens cloud game 1 during a ride, the game screen of cloud game 1 can be the user's game screen in this embodiment.
[0020] Step 102: Predict the state information of multiple objects in the vehicle's driving environment based on environmental information.
[0021] In the embodiments of this application, the multiple objects in the vehicle driving environment can be objects existing in the vehicle driving environment, such as pedestrians, vehicles, bicycles, mobility scooters, obstacles, etc. around the vehicle driving road.
[0022] In some examples, the state information of multiple objects may include, but is not limited to, pedestrian movement information, vehicle, autonomous vehicle, mobility scooter driving information, obstacle location information or movement information, etc.
[0023] It should be noted that, in the implementation of this application, the state information of multiple objects in the future can be predicted based on environmental information. That is, the state of multiple objects in the future can be predicted based on the current road conditions of the vehicle. For example, if the road is congested, it can be predicted that the vehicle in the road will slow down, suddenly change lanes, or brake suddenly. If there is a pedestrian crossing ahead, it can be predicted that pedestrians around the road will cross the road. And so on. No further examples will be given here.
[0024] Step 103: In response to the presence of a target object among multiple objects that changes the driving state of the vehicle, determine the driving state change data of the vehicle based on the state information of the target object.
[0025] In the embodiments of this application, the target object that changes the vehicle's driving state may include, but is not limited to, an object that suddenly appears and causes the vehicle to need to brake suddenly, an object that appears at a fixed speed and causes the vehicle to need to gradually decelerate, and traffic lights at intersections, etc.
[0026] In some examples, the vehicle's driving status change data may include, but is not limited to, changes in vehicle speed, changes in direction, changes in acceleration, etc. For instance, if the target object's status information corresponds to a slow-moving vehicle in front of the vehicle, then the vehicle's driving status change data could be changing lanes or accelerating to overtake the slow-moving vehicle; if the target object's status information corresponds to a traffic light changing from green to yellow and then to red, then the vehicle's driving status change data could be slowly decelerating; if the target object's status information corresponds to a pedestrian suddenly appearing to cross the road, then the vehicle's driving status change data could be urgently decelerating to avoid the pedestrian, and so on. Further examples will not be provided here.
[0027] Step 104: Update the game screen to the target dynamic game screen corresponding to the generated driving status change data.
[0028] Among them, the target dynamic game screen is used by users to perceive changes in the vehicle's driving status.
[0029] In this embodiment of the application, if the vehicle's driving state is a sudden acceleration or a sudden deceleration, the target dynamic game screen can be a screen with a sudden animation or a screen in which objects suddenly move. Based on the target game screen, the user can perceive the sudden acceleration or deceleration of the vehicle through vision.
[0030] In some examples, if the vehicle is accelerating or decelerating slowly, the target dynamic game screen can be a slowly appearing animation or a screen showing objects moving slowly. Based on the target game screen, the user can perceive the vehicle's slow acceleration or deceleration visually.
[0031] Compared with existing technologies, this embodiment acquires environmental information related to the vehicle's driving state and the user's game screen in the vehicle's cabin; predicts the state information of multiple objects in the vehicle's driving environment based on the environmental information; responds to the presence of a target object among the multiple objects that changes the vehicle's driving state, determines the vehicle's driving state change data based on the target object's state information; updates the game screen to generate a target dynamic game screen corresponding to the driving state change data, and the target dynamic game screen is used by the user to perceive the vehicle's driving state change; thus, this embodiment allows the user to perceive the vehicle's driving state change through the target game screen when the vehicle's driving state changes. Therefore, when the user plays games while traveling, they can perceive the vehicle's driving state change based on the target game screen, allowing the user's visual and inner ear systems to perceive similar driving state changes, thereby helping to reduce motion sickness and improving the user experience.
[0032] As a refinement and extension of the above embodiments, this embodiment provides a method for generating game screens, such as... Figure 2 As shown, the method includes: Step 201: Obtain environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin.
[0033] Optionally, when performing the task of "acquiring environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin", the following methods may be used, but are not limited to: acquiring environmental images of the vehicle's environment based on the vehicle's camera equipment; and identifying the environmental images to obtain environmental information related to the vehicle's driving status.
[0034] In this embodiment, the vehicle's camera equipment is one of the core perception components of intelligent driving, advanced driver assistance systems (ADAS), and vehicle-to-everything (V2X) communication. They achieve real-time perception and understanding of the surrounding environment by collecting visual information; for example, the vehicle's camera equipment can specifically be an in-vehicle camera.
[0035] In some examples, a pre-trained detection model can be used to identify and detect environmental images, thereby enabling the identification of street scenes from images captured by vehicle-mounted cameras. This is the environmental information related to the vehicle's driving state in this embodiment of the application. The street scene is a continuously evolving image of the vehicle's driving direction, such as houses, trees, landmarks, etc.
[0036] In this embodiment, the training process of the pre-trained detection model may include, but is not limited to, the following: collecting and preparing a dataset for training, which can be achieved by taking pictures of the vehicle's surroundings, downloading from the internet, or purchasing professional vehicle surroundings datasets, ensuring that the data source is reliable and meets the training objectives; building the model architecture, completing data training and optimization, repeating the training and optimization process until the model achieves satisfactory performance on the test dataset, and finally completing the detection model training.
[0037] As an alternative approach, the detection model trained in this embodiment of the application has the ability to identify street scenes, wherein street scenes may include, but are not limited to, fixed trees, mountains, buildings, etc. on both sides of the road. The training of the detection model may include, but is not limited to, the following steps: Step 1, collecting various street view images as a dataset, including scenes from different cities, rural roads, and different weather and lighting conditions. Open-source street view datasets such as Mapillary VistasDataset can be used, or the images can be collected independently; Step 2, labeling static objects such as roads, trees, mountains, and buildings for each image in the dataset. For example, annotation tools (such as LabelImg or VGG Image Annotator) can be used to annotate the bounding boxes of each object in the image; Step 3, selecting Faster R-CNN or YOLO as the base detection model; Step 4, preprocessing the dataset during training, including image resizing, normalization, and enhancement (such as random rotation, flipping, color adjustment, etc.) to increase the model's generalization ability; dividing the dataset into training, validation, and test sets, and selecting appropriate learning rates, loss functions, and optimizers to train Faster R-CNN or YOLO, obtaining the trained detection model. This object detection model has the ability to recognize street scenes (i.e., environmental information related to vehicle driving status in this embodiment of the application).
[0038] Optionally, after executing "acquiring environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin", the following method can be used, but is not limited to: generating a dynamic environmental image corresponding to the environmental information based on the screen type corresponding to the game screen; and compositing the dynamic environmental image as the background image of the game screen with the game screen.
[0039] In this embodiment of the application, the screen type corresponding to the game screen can be the style type of the game screen; for example, if the style type of game screen 1 is style 1, then the generated dynamic environment image is the image corresponding to style 1, and then the dynamic environment image can be used as the background image of the game screen to be synthesized with the game screen so that the synthesized background image and the game screen have the same style.
[0040] For example, based on the street scene identified by the target model (i.e., the environmental information related to the vehicle driving state in this application embodiment), the street scene image can be extracted from the captured image. Using the AIGC model, the street scene image can be used to generate a background image (i.e., the dynamic environment image in this application embodiment) that is similar to the style of the game screen. The background image is then used as the dynamic background of the in-vehicle cloud game and presented in the in-vehicle game (i.e., the game screen in this application embodiment).
[0041] It should be noted that the cloud server can identify the background on both sides of the characters or vehicles in the game, achieving layer overlay and realizing dynamic backgrounds. This way, when passengers see the changing scenery on both sides of the vehicle in their peripheral vision, they can also perceive similar changes in the in-vehicle cloud game, allowing passengers to quickly capture moving or changing images. Their eyes won't tell their brains that they are looking at a static, stable image, reducing motion sickness. Furthermore, in this embodiment, the game's dynamic background is generated only from the real-time street view outside the vehicle (i.e., static elements such as trees, buildings, and mountains). The game's dynamic background will not contain interfering elements such as pedestrians, non-motorized vehicles, or other vehicles, avoiding confusion with non-player characters (NPCs) in the game and affecting the user's gaming experience.
[0042] Step 202: Identify multiple objects in the vehicle's driving environment based on environmental information.
[0043] For example, based on the example in step 201, the multiple objects can be objects in the street scene (i.e., environmental information related to the vehicle driving state in this embodiment of the application) identified based on the target model, such as including but not limited to pedestrians, vehicles, bicycles, mobility scooters, obstacles, etc.
[0044] Step 203: Use the target model to predict the state information of multiple objects in the driving environment.
[0045] The target model is trained on a road video dataset and is used to predict the state information of different objects on the road.
[0046] In some examples, if a passenger opens an in-vehicle cloud game while the vehicle is in motion, the in-vehicle camera can capture images of the vehicle's direction of travel and the surrounding environment. Then, a pre-trained detection model is used to identify street scenes (i.e., environmental information related to the vehicle's driving state in this embodiment) from the captured images, and elements that may cause the vehicle to suddenly decelerate (i.e., target objects in this embodiment) are identified based on the target model.
[0047] In this embodiment, the target model has the ability to identify elements that may cause the vehicle to suddenly decelerate (i.e., target objects in this application embodiment). The elements that may cause the vehicle to suddenly decelerate (i.e., target objects in this application embodiment) may include, but are not limited to: a car that suddenly brakes in front of the vehicle, a car that suddenly cuts in front of the vehicle on the left (or right), a pedestrian or non-motorized vehicle that suddenly darts out from the left (or right) of the vehicle, etc.
[0048] As an optional approach, training the detection model may include, but is not limited to, the following steps: Step 1: First, collect data containing dynamic scenes, such as videos of vehicles braking suddenly, cars cutting in, pedestrians, or non-motorized vehicles suddenly crossing the road. This dataset may require actual filming under specific road conditions or data generated using a simulator. Step 2: Extract keyframes from the video and annotate the dynamic elements in each keyframe in detail, including the element's type, location, and direction of motion. Furthermore, the annotated data should include time-series information, such as the element's trajectory and speed changes. Step 3: Use Faster R-CNN and LSTM together to form the basic object detection model. Step 4: Define a time window during training (e.g., 5 consecutive frames as a time window), inputting 5 frames of images into Faster R-CNN. R-CNN outputs the predicted positions of various elements (such as cars, non-motorized vehicles, pedestrians, etc.) in the image and outputs the feature vectors of these elements. The feature vectors of consecutive frames are input into LSTM. After processing the input feature vectors, LSTM outputs the prediction results of the future state of each element, such as predicting whether each element will brake suddenly, cut in line suddenly, or suddenly dart out in the next few frames. Then, combining the LSTM's prediction results of the future state of each element with the Faster R-CNN's position detection results of each element, the elements in the image frame that may cause the vehicle to suddenly decelerate are predicted. Finally, based on the prediction results and the actual annotation, the loss value is calculated, and the model parameters are updated using the loss value to obtain the trained target model. This target model has the ability to identify elements that may cause the vehicle to suddenly decelerate (i.e., the target objects in this embodiment).
[0049] Step 204: In response to the presence of a target object among multiple objects that changes the driving state of the vehicle, determine the driving state change data of the vehicle based on the state information of the target object.
[0050] For example, if the target object corresponds to a car that suddenly brakes in front of the vehicle, the vehicle's driving state change data can be determined to be sudden braking based on the target object's state information (sudden braking); if the target object corresponds to a car that suddenly changes lanes to the left front (or right front) of the vehicle, the vehicle's driving state change data can be determined to be sudden braking or sudden lane change based on the target object's state information (sudden lane change); if the target object corresponds to a pedestrian or non-motorized vehicle that suddenly darts out to the left front (or right front) of the vehicle, the vehicle's driving state change data can be determined to be sudden braking or sudden lane change based on the target object's state information (sudden darts out).
[0051] For example, if the traffic light at the intersection where the target object is located is yellow and the status information of the target object is yellow, it can be determined that the vehicle's driving status change data is to brake slowly and then stop and wait; if the traffic light at the intersection where the target object is located is green and the status information of the target object is green and there are a few seconds left, it can be determined that the vehicle's driving status change data is to accelerate and then pass through the green light while ensuring safety, and so on. Examples will not be given here.
[0052] Step 205: Update the game screen to the target dynamic game screen corresponding to the generated driving status change data.
[0053] Among them, the target dynamic game screen is used by users to perceive changes in the vehicle's driving status.
[0054] Optionally, when executing "updating the game screen to the target dynamic game screen corresponding to the generated driving state change data", the following method can be used, but is not limited to this method: when the driving state change data meets the first change condition, generate an object animation based on the first speed, the object animation is used for the user to perceive the first driving state change of the vehicle; and combine the object animation and the game screen to obtain the target dynamic game screen.
[0055] In this embodiment of the application, the first change condition can be that the change in the vehicle's speed or acceleration exceeds the change threshold, that is, the vehicle is accelerating or decelerating rapidly. In this case, an object animation can be generated based on a relatively fast first speed, so that the user can perceive the rapid acceleration or deceleration of the vehicle based on the object animation, and avoid the user from feeling dizzy in the case of rapid acceleration or deceleration.
[0056] It should be noted that the first speed can be calculated based on the vehicle conditions or set according to user needs. The specific value of the first speed is not limited in this embodiment of the application.
[0057] For example, based on the example in step 203, for the identified element that may cause the vehicle to suddenly decelerate (i.e. the target object in this application embodiment), artificial intelligence generated content (AIGC) technology can be used to generate a monster that suddenly appears in front of the game view according to the style of the game screen. The user needs to attack or dodge this monster; thereby giving passengers a psychological warning that the vehicle they are riding in is about to brake or decelerate, thereby reducing the passengers' motion sickness.
[0058] Optionally, when executing "updating the game screen to the target dynamic game screen corresponding to the generated driving state change data", the following method can be used, but is not limited to this method: when the driving state change data meets the second change condition, generate a level animation based on the second speed, wherein the second speed is less than the first speed, and the level animation is used for the user to perceive the second driving state change of the vehicle; and combine the level animation and the game screen to obtain the target dynamic game screen.
[0059] In this embodiment of the application, the second change condition can be that the change in vehicle speed or acceleration does not exceed the change threshold, that is, the vehicle is slowly accelerating or slowly decelerating. In this case, a level animation can be generated based on a slower second speed, so that users can perceive the slow acceleration or slow deceleration of the vehicle based on the level animation, and avoid users from feeling dizzy when the vehicle is slowly accelerating or slowly decelerating.
[0060] It should be noted that the second speed can be a speed less than the first speed. The second speed can be calculated based on the vehicle conditions or set according to user needs. The specific value of the second speed is not limited in this embodiment of the application.
[0061] For example, based on the example in step 203, this embodiment of the application can also identify elements that cause the vehicle to slow down in advance based on real-time navigation information, such as intersections requiring turns, traffic lights requiring waiting, etc. Based on these elements, AIGC technology can be used to generate a slowly appearing level in front of the game's view, where the user needs to pause briefly and perform game operations. This gives passengers a psychological warning that the vehicle they are riding in will slow down, thereby reducing motion sickness.
[0062] Compared with existing technologies, this embodiment acquires environmental information related to the vehicle's driving state and the user's game screen in the vehicle's cabin; predicts the state information of multiple objects in the vehicle's driving environment based on the environmental information; responds to the presence of a target object among the multiple objects that changes the vehicle's driving state, determines the vehicle's driving state change data based on the target object's state information; updates the game screen to generate a target dynamic game screen corresponding to the driving state change data, and the target dynamic game screen is used by the user to perceive the vehicle's driving state change; thus, this embodiment allows the user to perceive the vehicle's driving state change through the target game screen when the vehicle's driving state changes. Therefore, when the user plays games while traveling, they can perceive the vehicle's driving state change based on the target game screen, allowing the user's visual and inner ear systems to perceive similar driving state changes, thereby helping to reduce motion sickness and improving the user experience.
[0063] Furthermore, as Figure 1 and Figure 2 The specific implementation of the method shown in this embodiment provides a device for generating game screens, such as... Figure 3 As shown, the device includes: an acquisition module 31, a prediction module 32, a determination module 33, and a generation module 34.
[0064] The acquisition module 31 is configured to acquire environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin. The prediction module 32 is configured to predict the driving environment of the vehicle based on the environmental information. The determination module 33 is configured to determine the driving state change data of the vehicle based on the state information of the target object in response to the existence of a target object among multiple objects that changes the driving state of the vehicle. The generation module 34 is configured to update the game screen to the target dynamic game screen corresponding to the generated driving state change data, wherein the target dynamic game screen is used by the user to perceive the changes in the driving state of the vehicle.
[0065] In some examples of this embodiment, the prediction module 32 is specifically configured to determine multiple objects existing in the driving environment of the vehicle based on the environmental information; and to predict the state information of the multiple objects in the driving environment using a target model, wherein the target model is trained based on a road video dataset and is used to predict the state information of different objects in the road.
[0066] In some examples of this embodiment, the generation module 34 is specifically configured to generate an object animation based on a first speed when the driving state change data meets a first change condition. The object animation is used by the user to perceive the first driving state change of the vehicle. The object animation and the game screen are combined to obtain a target dynamic game screen.
[0067] In some examples of this embodiment, the generation module 34 is further configured to generate a level animation based on a second speed when the driving state change data meets the second change condition, wherein the second speed is less than the first speed, and the level animation is used by the user to perceive the second driving state change of the vehicle; and the target dynamic game screen is obtained by combining the level animation and the game screen.
[0068] In some examples of this embodiment, the acquisition module 31 is specifically configured to acquire environmental images of the environment in which the vehicle is located based on the vehicle's camera device; and to identify the environmental images to obtain environmental information related to the vehicle's driving state.
[0069] In some examples of this embodiment, the acquisition module 31 is further configured to generate a dynamic environment image corresponding to the environment information based on the screen type corresponding to the game screen; and to synthesize the dynamic environment image as the background image of the game screen with the game screen.
[0070] It should be noted that other corresponding descriptions of the functional units involved in the game screen generation apparatus provided in this embodiment can be found in [reference needed]. Figure 1 and Figure 2 The corresponding descriptions in [the document] will not be repeated here.
[0071] Based on the above, Figure 1 and Figure 2 Accordingly, this embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. Figure 1 and Figure 2 The method shown.
[0072] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.
[0073] like Figure 4 The diagram shown is a hardware structure schematic of an electronic device according to the present invention, comprising: At least one processor 401; and, A memory 402 is communicatively connected to at least one of the processors 401; wherein, The memory 402 stores instructions that can be executed by at least one of the processors to enable at least one of the processors to perform the game screen generation method as described above.
[0074] Figure 4 Take a processor 401 as an example.
[0075] The electronic device may also include an input device 403 and an output device 404.
[0076] The processor 401, memory 402, input device 403, and output device 404 can be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.
[0077] Memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the game screen generation method in this embodiment of the application. Figure 1 and Figure 2 The method flow is shown. The processor 401 executes various functional applications and data processing by running non-volatile software programs, instructions, and modules stored in the memory 402, thereby realizing the game screen generation method in the above embodiment.
[0078] The memory 402 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created according to the method for generating game screens. Furthermore, the memory 402 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 402 may optionally include memory remotely located relative to the processor 401, and these remote memories may be connected via a network to the apparatus executing the method for generating game screens. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0079] Input device 403 can receive user clicks and generate signal inputs related to user settings and function controls for game screen generation methods. Output device 404 may include display devices such as a display screen.
[0080] When one or more modules are stored in the memory 402, and are run by one or more processors 401, the game screen generation method in any of the above method embodiments is executed.
[0081] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.
[0082] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.
[0083] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.
[0084] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms, or it can be implemented by hardware. By applying the solution of this embodiment, compared with the existing technology, this embodiment obtains environmental information related to the vehicle's driving state and the user's game screen in the vehicle's cabin; predicts the state information of multiple objects in the vehicle's driving environment based on the environmental information; responds to the existence of a target object among the multiple objects that changes the vehicle's driving state, determines the vehicle's driving state change data based on the target object's state information; updates the game screen to generate a target dynamic game screen corresponding to the driving state change data, and the target dynamic game screen is used by the user to perceive the vehicle's driving state change; thus, this embodiment can enable the user to perceive the vehicle's driving state change through the target game screen when the vehicle's driving state changes, and thus, when the user plays games during the ride, they can perceive the vehicle's driving state change based on the target game screen, so that the user's visual and inner ear systems feel similar driving state changes, thereby helping to reduce the user's motion sickness and improving the user experience.
[0085] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0086] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.
Claims
1. A method for generating game screens, characterized in that, include: Acquire environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin; Based on the environmental information, the state information of multiple objects in the vehicle's driving environment is predicted; In response to the presence of a target object among the plurality of objects that changes the driving state of the vehicle, the driving state change data of the vehicle is determined based on the state information of the target object. The game screen is updated to the target dynamic game screen corresponding to the generated driving state change data, and the target dynamic game screen is used by the user to perceive the changes in the vehicle's driving state.
2. The method according to claim 1, characterized in that, The prediction of the state information of multiple objects in the vehicle's driving environment based on the environmental information includes: Based on the environmental information, the multiple objects present in the vehicle's driving environment are determined; The target model is used to predict the state information of multiple objects in the driving environment. The target model is trained on a road video dataset and is used to predict the state information of different objects in the road.
3. The method according to claim 2, characterized in that, The step of updating the game screen to the target dynamic game screen corresponding to the generated driving state change data includes: When the driving state change data meets the first change condition, an object animation is generated based on the first speed. The object animation is used by the user to perceive the first driving state change of the vehicle. The target dynamic game screen is obtained by combining the object animation and the game screen.
4. The method according to claim 2, characterized in that, The step of updating the game screen to the target dynamic game screen corresponding to the generated driving state change data includes: When the driving state change data meets the second change condition, a level animation is generated based on the second speed, wherein the second speed is less than the first speed, and the level animation is used by the user to perceive the second driving state change of the vehicle; The target dynamic game screen is obtained by combining the level animation and the game screen.
5. The method according to claim 1, characterized in that, The acquisition of environmental information related to the vehicle's driving status includes: The vehicle's camera equipment acquires environmental images of the vehicle's surroundings. The environmental image is identified to obtain environmental information related to the vehicle's driving status.
6. The method according to any one of claims 1 to 5, characterized in that, After acquiring environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin, the method further includes: Generate a dynamic environment image corresponding to the environment information based on the screen type corresponding to the game screen. The dynamic environment image is used as the background image of the game screen and combined with the game screen.
7. A device for generating game screens, characterized in that, include: The acquisition module is configured to acquire environmental information related to the vehicle's driving status and the user's game screen in the vehicle's cabin; The prediction module is configured to predict the state information of multiple objects in the vehicle's driving environment based on the environmental information. The determination module is configured to determine the driving state change data of the vehicle based on the state information of the target object in response to the existence of a target object among the plurality of objects that changes the driving state of the vehicle. The generation module is configured to update the game screen to the target dynamic game screen corresponding to the generated driving state change data, the target dynamic game screen being used by the user to perceive the changes in the vehicle's driving state.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.
9. An electronic device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.
10. A computer program product, the computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 6.