Vehicle cabin photographing guiding method and device, electronic equipment and storage medium

Abstract

The invention provides a vehicle cabin photographing guiding method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring data of a vehicle based on a perception sensor of the vehicle; wherein the data of the vehicle comprises environment data and state data; determining an optimization demand based on the data of the vehicle and the photographing scene; generating guidance information based on the optimization demand, and prompting the guidance information through a human-computer interaction interface or voice; determining a photographing mode based on the optimization demand, and adjusting parameters of camera equipment and related equipment of the vehicle cabin based on the photographing mode; an image is captured by a camera device. In the mode, the user can be assisted in optimizing the photographing parameters and postures through the data collected by the perception sensor of the vehicle, and the in-vehicle photographing experience is improved.

Description

Technical Field

[0001] This invention relates to the field of human-computer interaction technology, and in particular to a method, device, electronic device, and storage medium for guiding vehicle cockpit photography. Background Technology

[0002] With the development of intelligent vehicles, the functions of vehicle cabins are becoming increasingly diverse, and users' activities inside the car are also becoming more varied. During driving or rest stops, users often have needs for taking photos, such as selfies, live streaming, and shooting vlogs (video blogs). Currently, in-vehicle cameras are limited by factors such as placement angles and performance parameters, which cannot meet user needs; therefore, users are more accustomed to using their own collected photos for filming.

[0003] However, taking photos inside a car presents several inconveniences for users: Firstly, limited interior space makes it difficult for users to quickly find the best shooting position using their experience. Furthermore, the significant differences in cabin layout between different car models increase the difficulty of finding the optimal spot. For example, in some compact vehicles, the small distance between the seats and the center console makes it easy for users to be limited by space when trying different angles with their phones, preventing them from obtaining the ideal shooting perspective. Secondly, the complex lighting conditions inside a car, influenced by factors such as window transmittance, the angle of sunlight, and the arrangement of interior lights, make it difficult for ordinary users to accurately determine how to adjust their phone's camera parameters (such as exposure and white balance) to obtain high-quality photos. For instance, on a sunny afternoon, sunlight streaming directly into the car through the windows creates overly bright areas, easily leading to overexposed photos if taken directly. Simultaneously, current technology lacks a systematic and intelligent approach that can comprehensively utilize the vehicle's sensor information to provide users with comprehensive and accurate guidance for mobile phone photography. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a vehicle cabin photography guidance method, device, electronic device and storage medium, so as to assist users in optimizing photography parameters and postures by using data collected by the vehicle's perception sensors, thereby improving the in-vehicle photography experience.

[0005] In a first aspect, embodiments of the present invention provide a vehicle cabin photography guidance method, the method comprising: collecting vehicle data based on the vehicle's perception sensors; wherein the vehicle data includes: environmental data and status data; determining optimization requirements based on the vehicle data and the photography scene; generating guidance information based on the optimization requirements, and providing guidance information through a human-computer interaction interface or voice prompts; determining a photography mode based on the optimization requirements, and adjusting the parameters of the camera device and related equipment in the vehicle cabin based on the photography mode; and capturing images using the camera device.

[0006] In optional embodiments of this application, the steps of collecting vehicle data based on vehicle perception sensors include at least one of the following: collecting light intensity and color temperature data inside or outside the vehicle based on a light sensor installed in the vehicle cabin; identifying mobile phone location data based on a camera, time-of-flight sensor, and millimeter-wave radar inside the vehicle cabin; collecting seat position data based on a displacement sensor at the bottom of the vehicle cabin; obtaining steering wheel position data based on a steering wheel angle sensor; obtaining sunroof status data based on the vehicle's sunroof control module; obtaining time data based on the vehicle's onboard clock; obtaining direction data based on the vehicle's positioning module; and obtaining real-time map data based on the vehicle's navigation system.

[0007] In an optional embodiment of this application, the step of determining optimization requirements based on vehicle data and photo scenes includes: acquiring photo scenes input by the user through a human-computer interaction interface or voice; inputting the vehicle data and photo scenes into the vehicle's decision center for data fusion analysis, and outputting optimization requirements.

[0008] In optional embodiments of this application, the aforementioned optimization requirements include: lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements. The step of inputting vehicle data and the shooting scene into the vehicle's decision center for data fusion analysis and outputting optimization requirements includes: inputting vehicle data and the shooting scene into the vehicle's decision center; the decision center determining a light intensity threshold range as a lighting optimization requirement based on the vehicle data and the shooting scene; the decision center determining the user's line of sight height during shooting as a viewing angle optimization requirement based on the vehicle data and the shooting scene; the decision center determining scene adaptation requirements that adapt to map data and time data based on the vehicle data and the shooting scene; and the decision center outputting the lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements.

[0009] In optional embodiments of this application, the steps of providing guidance information through a human-computer interaction interface or voice prompts include: displaying guidance information through images or text via a human-computer interaction interface; and playing guidance information via voice through a vehicle audio system.

[0010] In optional embodiments of this application, the above-mentioned photo-taking modes include: selfie mode, video blog mode, and scenery mode; the step of adjusting the parameters of the camera equipment and related equipment in the vehicle cabin based on the photo-taking mode includes: adjusting the mobile phone camera parameters, sunroof opening parameters, and seat angle parameters based on the photo-taking mode.

[0011] In an optional embodiment of this application, after the above-described step of capturing images with a camera device, the method further includes: evaluating the image capture effect, determining whether there is a capture problem based on the capture effect; if there is a capture problem, generating guidance information and / or adjusting the parameters of the camera device and related equipment in the vehicle cabin based on the capture problem; and recapture the image with the camera device.

[0012] Secondly, embodiments of the present invention also provide a vehicle cabin photography guidance device, the device comprising: a data perception and acquisition module for collecting vehicle data based on the vehicle's perception sensors; wherein the vehicle data includes environmental data and status data; a scene analysis and decision-making module for determining optimization requirements based on the vehicle data and the photography scene; a guidance generation module for generating guidance information based on the optimization requirements, and providing guidance information through a human-computer interaction interface or voice prompts; a mode recommendation module for determining a photography mode based on the optimization requirements, and adjusting the parameters of the camera equipment and related equipment in the vehicle cabin based on the photography mode; and an execution feedback module for capturing images through the camera equipment.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the above-described vehicle cabin photography guidance method.

[0014] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are invoked and executed by a processor, the computer-executable instructions cause the processor to implement the above-described vehicle cockpit photography guidance method.

[0015] The embodiments of the present invention bring the following beneficial effects: This invention provides a vehicle cabin photography guidance method, device, electronic device, and storage medium. Based on the vehicle's perception sensors, it collects vehicle data, including environmental and status data. Based on the vehicle data and the photography scene, it determines optimization requirements; based on these requirements, it generates guidance information, which is then displayed via a human-machine interface or voice prompts; based on the optimization requirements, it determines the photography mode and adjusts the parameters of the camera and related vehicle cabin equipment; finally, it captures an image using the camera. This method utilizes data collected by the vehicle's perception sensors to assist users in optimizing photography parameters and posture, thus improving the in-vehicle photography experience.

[0016] Other features and advantages of this disclosure will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the techniques described above.

[0017] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a vehicle cabin photography guidance method provided in an embodiment of the present invention; Figure 2 A flowchart of another vehicle cabin photography guidance method provided in an embodiment of the present invention; Figure 3 A schematic diagram of the system hardware architecture for providing mobile phone photography guidance in the cockpit of an intelligent vehicle, provided as an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a vehicle cabin photography guidance device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Currently, existing mobile phone photography technology mainly suffers from the following shortcomings: 1. Poor environmental adaptability: The interior lighting is significantly affected by various factors such as time, weather, sunroof status, and vehicle direction (e.g., dim interior lighting when driving against the light, or glaring light when the midday sun is shining directly on the vehicle). Current mobile phone photography technology does not incorporate environmental data collected by vehicle sensors, resulting in photos that are prone to overexposure, underexposure, and reflection.

[0022] 2. Cumbersome operation: Ordinary users often lack professional photography knowledge and find it difficult to accurately adjust the position of the mobile phone (such as angle and height) and camera parameters (such as ISO and shutter speed) according to the in-car environment. The manual adjustment process is not only time-consuming, but the results are often unsatisfactory.

[0023] 3. Insufficient scene coverage: There are many different scenarios for taking photos inside the car (selfies, shooting the scenery outside the car, recording details inside the cabin, etc.), and the existing technology does not provide personalized guidance for different scenarios, which cannot meet the diverse needs of users.

[0024] 4. Failure to utilize vehicle sensors to collect data: The position of the seats and steering wheel in the vehicle cabin can be adjusted to optimize the shooting angle, the sunroof can adjust the amount of light entering, and map information can suggest the best shooting location. However, the current technology does not link these resources with the needs of photography, resulting in a waste of functionality.

[0025] Therefore, existing mobile phone photography technology suffers from problems such as poor environmental adaptability, cumbersome operation, insufficient scene coverage, and underutilization of cockpit resources.

[0026] Based on this, the present invention provides a vehicle cabin photography guidance method, device, electronic device and storage medium, which mainly relates to the field of human-computer interaction in intelligent vehicles. Specifically, it provides an intelligent vehicle cabin photography guidance method based on multi-sensor fusion, which can assist users in optimizing photography parameters and postures by using data collected by the vehicle's perception sensors, thereby improving the in-vehicle photography experience.

[0027] To facilitate understanding of this embodiment, a vehicle cabin photography guidance method disclosed in this embodiment of the invention will first be described in detail.

[0028] Example 1: This invention provides a method for guiding users to take photos in a vehicle cabin, which optimizes the user experience of taking photos with a mobile phone inside the vehicle. See [link to relevant documentation]. Figure 1 The flowchart shown illustrates a method for guiding vehicle cabin photography, which includes the following steps: Step S102: Based on the vehicle's perception sensors, collect vehicle data; wherein, the vehicle data includes: environmental data and status data.

[0029] In this embodiment, the vehicle's environmental and status data can be collected through the vehicle's perception sensors, including information such as light intensity, seat position, steering wheel position, sunroof status, time, vehicle direction, and real-time map.

[0030] Step S104: Determine optimization requirements based on vehicle data and photography scenarios.

[0031] In this embodiment, the optimization needs of the current shooting environment can be analyzed based on the vehicle data collected by the perception sensor and the user's shooting scenario (e.g., selfie, live broadcast, vlog, etc.), and a shooting optimization model can be built through the vehicle's decision center.

[0032] Step S106: Generate guidance information based on optimization requirements, and provide guidance information through human-computer interaction interface or voice prompts.

[0033] In this embodiment, guidance information can also be generated based on optimization requirements. The guidance information can be provided through human-machine interface (HMI) prompts or voice prompts to guide users to adjust the position of their mobile phone, camera parameters, vehicle position, or seat position.

[0034] Step S108: Determine the shooting mode based on optimization requirements, and adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the shooting mode.

[0035] In this embodiment, an algorithm can be used to recommend shooting modes suitable for the scene. After the user selects a mode, the parameters of the camera equipment and related equipment in the vehicle cabin will be automatically adjusted without the need for manual operation by the user.

[0036] Step S110: Capture an image using a camera device.

[0037] In this embodiment, images can be captured using a camera device. After capturing the images, evaluation and feedback can be performed based on them.

[0038] This invention provides a vehicle cabin photography guidance method, which collects vehicle data based on the vehicle's perception sensors. This data includes environmental and status data. Optimization requirements are determined based on the vehicle data and the photography scene. Guidance information is generated based on these requirements and provided through a human-machine interface or voice prompts. A photography mode is determined based on the optimization requirements, and parameters of the camera and related vehicle cabin equipment are adjusted accordingly. Finally, an image is captured using the camera. This method utilizes data collected by the vehicle's perception sensors to assist users in optimizing photography parameters and posture, thereby improving the in-vehicle photography experience.

[0039] Example 2: This embodiment provides another method for guiding vehicle cabin photography, which is implemented based on the above embodiment. See also... Figure 2 The flowchart shown illustrates another method for guiding vehicle cabin photography, which includes the following steps: Step S202: Based on the vehicle's perception sensors, collect vehicle data; wherein, the vehicle data includes: environmental data and status data.

[0040] See also Figure 3 The diagram shows a hardware architecture schematic of a system for providing mobile phone photography guidance within the cockpit of a smart vehicle. Figure 3As shown, the hardware architecture of the intelligent vehicle cockpit's mobile phone photo-taking guidance system includes: a multi-modal perception layer, a decision center, and a multi-modal execution layer. The multi-modal perception layer and the decision center are connected via a CAN (Controller Area Network) / LIN (Local Interconnect Network) bus, while the decision center and the multi-modal execution layer are connected via 5G (Fifth Generation Mobile Communication Technology) / V2X (Vehicle-to-Everything).

[0041] like Figure 3 As shown, the multi-mode perception layer may include: vehicle sensors such as light, seats, directions, and radar; positioning modules such as GPS (Global Positioning System) and high-precision maps; and vision systems such as external and internal cameras.

[0042] like Figure 3 As shown, the decision center may include: a data integration module for spatiotemporal calibration, a scene understanding engine for deep learning classification, and a parameter optimizer for photophysical models.

[0043] like Figure 3 As shown, the multimodal execution layer may include: voice, HMI and other guided interaction modules, various execution modules for electric adjustment, and Bluetooth and WiFi (Wireless Fidelity) as mobile phone linkage interfaces.

[0044] like Figure 3 As shown, the multi-mode perception layer of the vehicle in this embodiment can acquire at least one of the following data through various perception sensors: (1) Data on light intensity and color temperature inside or outside the vehicle are collected by light sensors installed in the vehicle cabin.

[0045] This embodiment can collect the brightness of light inside or outside the vehicle, measured in lux, using a light sensor installed in the cabin (such as a light sensor located above the dashboard or a light and rain sensor on the vehicle body). It can also collect the color temperature, measured in Kelvin, using a light sensor installed in the cabin, with a sampling frequency of 10Hz or higher. High-frequency sampling allows for timely capture of dynamic changes in light, providing precise data support for subsequent light adjustment.

[0046] In addition, this embodiment can also use the light sensor of a mobile phone to replace the light sensor in the vehicle to collect the brightness of light inside or outside the vehicle.

[0047] (2) Identify mobile phone location data based on cameras, time-of-flight sensors and millimeter-wave radar in the vehicle cabin.

[0048] This embodiment can identify the specific location of the mobile phone using cameras, TOF (Time-of-Flight) sensors, and millimeter-wave radar in the vehicle's cabin, and use this information as a reference for subsequent adjustments to the phone's location.

[0049] (3) Collect seat position data based on displacement sensors at the bottom of the vehicle cabin.

[0050] This embodiment uses a displacement sensor at the bottom of the seat to collect the seat's fore-aft distance, height, and backrest angle. High-precision seat position data accurately reflects the user's posture and position inside the vehicle, helping to recommend suitable shooting angles.

[0051] (4) Obtain the position data of the steering wheel based on the vehicle's steering wheel angle sensor.

[0052] This embodiment uses a steering wheel angle sensor to obtain the current steering wheel angle, which is used to determine the driver's hand movement space when taking a picture. For example, when the steering wheel angle is large, the driver's hand movement is restricted, and a more convenient shooting position or method can be recommended.

[0053] (5) Obtain sunroof status data based on the vehicle's sunroof control module.

[0054] This embodiment can obtain the sunroof opening degree (0-100%) and whether the sunshade is open through the sunroof control module. The sunroof status directly affects the amount of light entering the vehicle and is an important parameter for adjusting the interior lighting.

[0055] (6) Obtain time data based on the vehicle clock.

[0056] This embodiment can obtain the current time through the vehicle's onboard clock.

[0057] (7) Obtain direction data based on the vehicle's positioning module.

[0058] This embodiment can obtain the vehicle's driving direction (0° is due north, increasing clockwise) through the vehicle's positioning module (e.g., GPS). The time and direction information can be combined with the geographical location to determine the sun's position, thereby predicting the trend of light changes.

[0059] In addition, this embodiment can also use the positioning module of a mobile phone to replace the positioning module in the vehicle to collect directional data.

[0060] (8) Obtain real-time map data based on the vehicle navigation system.

[0061] This embodiment can obtain the current geographical location (such as urban roads, mountainous areas, coastal highways) and surrounding environmental tags (such as "scenic spots" and "backlit areas") through the vehicle navigation system. The map information can recommend the best shooting locations for users, improving shooting results.

[0062] For example, when a vehicle is traveling on a coastal highway at 3 PM, the GPS displays a "Coastal Highway" tag, the direction sensor shows the vehicle is facing southwest (at a 30° angle to the sun), the light sensor detects an interior light intensity of 3000 lux (strong light condition), a color temperature of 5400K, and the sunroof is closed. At this point, the system can determine that the interior light is too strong and there may be a backlighting issue, and therefore recommends opening the sunshade or adjusting the shooting angle.

[0063] Step S204: Determine optimization requirements based on vehicle data and photography scenarios.

[0064] In some embodiments, the user can obtain the photo scene through a human-computer interaction interface or voice input; the vehicle data and the photo scene are input into the vehicle's decision center for data fusion analysis, and optimization requirements are output.

[0065] In this embodiment, the user-inputted photo-taking scenario can be obtained first through HMI or voice interaction. For example, the user can voice-input "I want to take a selfie" or select "Vlog mode" in the HMI. After determining the photo-taking scenario, the vehicle data obtained in the aforementioned steps is then used... Figure 3 The decision-making center in the system performs data fusion analysis.

[0066] In some embodiments, the above optimization requirements include: lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements; vehicle data and shooting scene can be input into the vehicle's decision center; the decision center determines the light intensity threshold range as the lighting optimization requirement based on the vehicle data and shooting scene; the decision center determines the user's line of sight height when shooting as the viewing angle optimization requirement based on the vehicle data and shooting scene; the decision center determines the scene adaptation requirements that adapt to map data and time data based on the vehicle data and shooting scene; the decision center outputs the lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements.

[0067] (1) Lighting optimization requirements: Set a light intensity threshold range, where the optimal light intensity for selfie scenes is 500-1500 lux, and the optimal light intensity for landscape photography is 1000-4000 lux. When the detected light intensity is below the lower limit (e.g., 80 lux in the car interior), it is determined that the light input needs to be increased; when it is above the upper limit (e.g., 5000 lux), it is determined that the direct strong light needs to be reduced. The above specific values ​​can also be dynamically adjusted according to the actual vehicle calibration.

[0068] (2) Viewpoint optimization requirements: Calculate the user's eye level (seat height + user posture correction value) based on the seat position. If the eye level is lower than the optimal angle of the phone lens (e.g., the lens needs to be level with the face when taking a selfie), it is determined that the seat height or phone position needs to be adjusted. By accurately calculating the difference between the eye level and the optimal lens angle, specific adjustment suggestions can be provided to the user.

[0069] (3) Scene adaptation requirements: Based on map information and time, if the map label is "scenic spot" and the time is during the golden shooting period (such as 1 hour after sunrise), it is determined that "scenery mode along the way" should be recommended, and the vehicle position should be adjusted to a place with a wide view. The light during the golden shooting period is soft, which can produce better photos, while a wide view can include more scenic elements.

[0070] For example, if a user selects "selfie mode," and the light sensor detects an interior light level of 400 lux (below the 500 lux lower limit), and the seat position data shows the user's eye level is 120cm (the phone camera's current height is 100cm), then the optimization requirement output by the decision center could be: "Increase interior light and raise the phone camera height to 120cm." This optimization requirement clearly defines the parameters and target values ​​that need to be adjusted, providing a basis for subsequent guidance.

[0071] Step S206: Generate guidance information based on optimization requirements, and provide guidance information through a human-computer interaction interface or voice prompts.

[0072] In this embodiment, guidance information can be generated and prompted to the user based on optimization requirements.

[0073] In some embodiments, guidance information can be displayed via images or text through a human-computer interaction interface; guidance information can also be played via voice through the vehicle's audio system.

[0074] Figure 3 The guided interaction module can generate specific guidance content based on the optimization requirements obtained from the preceding steps, providing prompts through both HMI and voice channels: (1) HMI prompts: Graphic and text instructions are displayed on the central control screen. For example, when the light is insufficient, it is recommended to open the sunroof to 50% and mark the sunroof control area. When adjusting the position of the mobile phone, a real-time virtual frame is displayed, prompting "Move the mobile phone up 20cm and turn it 15° to the left". The combination of graphics and text is more intuitive, and users can quickly understand and perform the adjustment operation.

[0075] (2) Voice prompts: Natural language guidance is played through the car audio system, such as "Backlight detected, it is recommended to adjust the seat back 5° to avoid facial shadows." Voice prompts can provide guidance when it is inconvenient for users to look at the screen, improving the convenience of operation.

[0076] Meanwhile, the guidance on camera parameter adjustments is detailed down to specific values, such as: "The current light is low, so we recommend adjusting the phone's ISO to 400 and exposure compensation to +0.7," and "When shooting moving subjects, we recommend setting the shutter speed to 1 / 500s." These specific parameter recommendations are based on professional photography knowledge and extensive experimental data, helping users quickly set appropriate camera parameters.

[0077] For example, considering the needs of selfie scenarios, the HMI can display a sunroof icon and a diagram illustrating the phone's position adjustment, with simultaneous voice prompts such as, "Please open the sunroof to 30% and hold the phone at eye level." This multi-channel prompting method ensures that users accurately understand and follow the instructions, improving adjustment efficiency.

[0078] Step S208: Determine the shooting mode based on optimization requirements, and adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the shooting mode.

[0079] In this embodiment, the shooting mode can also be determined based on optimization requirements. Figure 3 Each execution module can automatically adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the shooting mode after the user makes a selection.

[0080] In some embodiments, the photo-taking modes include: selfie mode, video blog mode, and scenic view mode; the phone camera parameters, sunroof opening parameters, and seat angle parameters can be adjusted based on the photo-taking mode.

[0081] In this embodiment, a preset algorithm can recommend a shooting mode that suits the scene. After the user selects the mode, the phone camera parameters and related cabin equipment (such as sunroof opening parameters and seat angle parameters) are automatically adjusted without the need for manual operation by the user.

[0082] (1) Selfie mode: This embodiment can automatically adjust the phone camera parameters (medium beauty level, exposure compensation +0.3, focal length 35mm), and link the seat adjustment module to fine-tune the seat back to 105° (a comfortable shooting angle). If the light is insufficient, it will automatically turn on the cabin ambient light (brightness adjusted to 80%). The medium beauty level can preserve the user's natural features while enhancing their appearance; the 105° seat back angle has been ergonomically tested to allow users to maintain a comfortable posture when taking selfies.

[0083] (2) Vlog mode: This embodiment can automatically activate the phone's image stabilization function, recommends a video frame rate of 60fps, and judges the driver's operating space based on the steering wheel position, prompting "If the steering wheel angle is less than 30°, you can fix the phone to the center console bracket," and automatically adjusts the sunroof opening to 20% (to balance light and wind noise). The 60fps video frame rate ensures smooth video playback, suitable for post-editing; the 20% sunroof opening allows in some light while avoiding excessive wind noise affecting video recording.

[0084] (3) Scenery along the way: This embodiment can use GPS positioning to recommend the best parking spot (such as a viewing platform 500m ahead), automatically switch the phone camera to wide-angle mode (24mm focal length), and adjust the sunroof to be fully open to increase light intake. If the vehicle is facing the light from the opposite direction, it will prompt "It is recommended to turn 30° to the right to avoid lens glare". Wide-angle mode can capture a wider landscape; a fully open sunroof can maximize the introduction of natural light, improving the brightness and color reproduction of the photos.

[0085] The automatic adjustment relies on wireless communication between the vehicle's infotainment system and the mobile phone (such as Bluetooth or WiFi). The vehicle's infotainment system sends parameter adjustment commands to the mobile phone via a preset API (Application Programming Interface), and the mobile phone's camera app automatically updates the settings upon receiving the commands. For example, if the user selects "Vlog mode," the vehicle's infotainment system sends the command to the mobile phone: "Frame rate = 60fps, image stabilization = on, focal length = 28mm," while the cockpit system automatically moves the seat forward by 10cm to expand the shooting field of view. This automatic adjustment method eliminates the tedious process of manually setting parameters, improving the convenience of shooting.

[0086] Step S210: Capture an image using a camera device.

[0087] In this embodiment, images of the interior or exterior of the vehicle can be captured using a camera device. After capturing the images, this embodiment can also perform evaluation and feedback based on the captured images.

[0088] Step S212: Evaluate the image capture quality and determine whether there are any capture problems based on the capture quality; if there are capture problems, generate guidance information and / or adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the capture problems; recapture the image using the camera equipment.

[0089] In this embodiment, after taking a photo, the image shooting effect can be evaluated through image analysis technology (calling the mobile phone's photo preview image) to determine whether there are any shooting problems.

[0090] If there are no shooting problems, it means that the exposure of the test photo is normal and the subject is clear, and the feedback is "The photo effect is good, and the current parameters can be saved as the commonly used settings"; if there are shooting problems (such as shadows or blur), the guidance information can be generated: "Face shadows detected, it is recommended to open the sunroof by 20%", and the image can be retaken through the camera equipment.

[0091] Simultaneously, it can record user operating habits and environmental data, and optimize the accuracy of subsequent guidance through machine learning. For example, if a user repeatedly chooses to manually lower the exposure in backlit scenes, the system will automatically lower the default exposure compensation for backlit mode by 0.3. By continuously learning user operating habits, the system can provide more personalized guidance and improve the user experience.

[0092] In addition, this embodiment can also use V2X communication to link drones to achieve third-person follow-up shooting outside the vehicle, or it can use AR (Augmented Reality) real-scene fusion technology to guide users to move their mobile phones or vehicles, making the operation more convenient and the success rate higher.

[0093] The vehicle cabin photography guidance method provided in this invention can comprehensively collect environmental and status data of the cabin through the vehicle's perception sensors, making the photography guidance more closely aligned with the dynamic in-vehicle scene and solving the problem of poor environmental adaptability in existing technologies. It simplifies user operation through HMI and voice prompts, lowering the barrier to entry for professional photography knowledge, allowing ordinary users to quickly adjust to their optimal state. Personalized recommendation modes are provided for different scenarios such as selfies, live streaming, and vlogs, covering diverse needs. Simultaneously, it integrates with cabin equipment such as seats and sunroofs, fully utilizing vehicle resources to enhance photo effects and meet users' high-quality needs for personalized in-vehicle photography.

[0094] Example 3: Corresponding to the above method embodiments, this invention provides a vehicle cabin photography guidance device, see [link to relevant documentation]. Figure 4 The diagram shows a structural schematic of a vehicle cabin photography guidance device, which includes: The data perception and acquisition module 41 is used to collect vehicle data based on the vehicle's perception sensors; the vehicle data includes environmental data and status data. Scene analysis and decision module 42 is used to determine optimization requirements based on vehicle data and photography scenes; The guidance generation module 43 is used to generate guidance information based on optimization requirements and provide guidance information through a human-computer interaction interface or voice prompts. The mode recommendation module 44 is used to determine the shooting mode based on optimization requirements and adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the shooting mode. The execution feedback module 45 is used to capture images via a camera device.

[0095] This invention provides a vehicle cabin photography guidance device that collects vehicle data based on the vehicle's perception sensors. This vehicle data includes environmental and status data. Based on the vehicle data and the photography scene, optimization requirements are determined. Guidance information is generated based on these optimization requirements and provided through a human-machine interface or voice prompts. A photography mode is determined based on the optimization requirements, and the parameters of the camera and related vehicle cabin equipment are adjusted accordingly. Finally, an image is captured using the camera. This method utilizes data collected by the vehicle's perception sensors to assist users in optimizing photography parameters and posture, thereby improving the in-vehicle photography experience.

[0096] The aforementioned data sensing and acquisition module is used for at least one of the following: acquiring light intensity and color temperature data inside or outside the vehicle based on a light sensor installed in the vehicle cabin; identifying mobile phone location data based on a camera, time-of-flight sensor, and millimeter-wave radar inside the vehicle cabin; collecting seat position data based on a displacement sensor at the bottom of the vehicle cabin; acquiring steering wheel position data based on a steering wheel angle sensor; acquiring sunroof status data based on the vehicle's sunroof control module; acquiring time data based on the vehicle's onboard clock; acquiring direction data based on the vehicle's positioning module; and acquiring real-time map data based on the vehicle's navigation system.

[0097] The aforementioned scenario analysis and decision-making module is used to acquire the photo-taking scenarios input by the user through the human-computer interaction interface or voice input; input the vehicle data and photo-taking scenarios into the vehicle's decision center for data fusion analysis, and output optimization requirements.

[0098] The aforementioned optimization requirements include: lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements. The aforementioned scene analysis and decision-making module is used to input vehicle data and shooting scene into the vehicle's decision center. The decision center determines the light intensity threshold range as the lighting optimization requirement based on the vehicle data and shooting scene. The decision center determines the user's line of sight height when shooting as the viewing angle optimization requirement based on the vehicle data and shooting scene. The decision center determines the scene adaptation requirements for adapting to map data and time data based on the vehicle data and shooting scene. The decision center outputs the lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements.

[0099] The aforementioned guidance generation module is used to display guidance information through images or text via a human-computer interaction interface, and to play guidance information via voice through the vehicle's audio system.

[0100] The aforementioned photo modes include: selfie mode, video blog mode, and scenic view mode; the aforementioned mode recommendation module is used to adjust the phone camera parameters, sunroof opening parameters, and seat angle parameters based on the photo mode.

[0101] The aforementioned execution feedback module is also used to evaluate the image capture effect, determine whether there is a capture problem based on the capture effect; if a capture problem exists, generate guidance information and / or adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the capture problem; and recapture the image using the camera equipment.

[0102] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the vehicle cabin photography guidance device described above can be referred to the corresponding process in the embodiments of the aforementioned vehicle cabin photography guidance method, and will not be repeated here.

[0103] Example 4: This invention also provides an electronic device for running the above-described vehicle cabin photography guidance method; see [link to related documentation]. Figure 5 The diagram shows the structure of an electronic device, which includes a memory 100 and a processor 101. The memory 100 is used to store one or more computer instructions, which are executed by the processor 101 to implement the above-mentioned vehicle cabin photography guidance method.

[0104] Furthermore, Figure 5 The electronic device shown also includes a bus 102 and a communication interface 103, with the processor 101, the communication interface 103 and the memory 100 connected via the bus 102.

[0105] The memory 100 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 103 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 102 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0106] Processor 101 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 101 or by instructions in software form. Processor 101 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 100, and processor 101 reads information from memory 100 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0107] This invention also provides a computer-readable storage medium storing computer-executable instructions. When these computer-executable instructions are called and executed by a processor, they cause the processor to implement the above-described vehicle cockpit photography guidance method. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0108] The computer program products of the vehicle cabin photography guidance method, device and electronic device provided in the embodiments of the present invention include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and / or device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0110] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0111] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0112] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0113] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for guiding vehicle cabin photography, characterized in that, The method includes: Based on the vehicle's perception sensors, data of the vehicle is collected; wherein, the vehicle data includes: environmental data and status data; Optimization requirements are determined based on the vehicle data and the photography scenario. Based on the optimization requirements, guidance information is generated, and the guidance information is prompted through a human-computer interaction interface or voice prompts. Based on the optimization requirements, a shooting mode is determined, and the parameters of the camera equipment and related equipment in the vehicle cabin are adjusted based on the shooting mode. Images are captured using the camera device.

2. The method according to claim 1, characterized in that, The step of collecting data from the vehicle based on its perception sensors includes at least one of the following: Light intensity and color temperature data are collected from inside or outside the vehicle using light sensors installed in the vehicle cabin. The location data of the mobile phone is identified based on the camera, time-of-flight sensor and millimeter-wave radar in the vehicle's cockpit. Seat position data is collected using displacement sensors located at the bottom of the vehicle cabin; The steering wheel position data is obtained based on the vehicle's steering wheel angle sensor; The sunroof status data is obtained based on the vehicle's sunroof control module. Time data is obtained based on the vehicle's onboard clock; Directional data is obtained based on the vehicle's positioning module; Real-time map data is obtained based on the vehicle navigation system.

3. The method according to claim 1, characterized in that, The steps for determining optimization requirements based on the vehicle data and the photography scene include: Acquire the scene of the photo taken by the user through the human-computer interaction interface or voice input; The vehicle data and the photographed scene are input into the vehicle's decision center for data fusion analysis, and optimization requirements are output.

4. The method according to claim 3, characterized in that, The optimization requirements include: lighting optimization requirements, viewing angle optimization requirements, and scene adaptation requirements; the steps of inputting the vehicle data and the shooting scene into the vehicle's decision center for data fusion analysis and outputting optimization requirements include: The vehicle data and the photographed scene are input into the vehicle's decision center; The decision center determines the light intensity threshold range as the light optimization requirement based on the vehicle data and the shooting scene; The decision center determines the user's eye level when taking the picture as the angle optimization requirement based on the vehicle data and the shooting scene. The decision center determines the scene adaptation requirements for the map data and time data based on the vehicle data and the shooting scene. The decision center outputs the lighting optimization requirements, the viewing angle optimization requirements, and the scene adaptation requirements.

5. The method according to claim 1, characterized in that, The steps of providing guidance information through a human-computer interaction interface or voice prompts include: The guidance information is displayed via images or text through a human-computer interaction interface; The guidance information will be played via voice prompts through the car's audio system.

6. The method according to claim 1, characterized in that, The photo-taking modes include: selfie mode, video blog mode, and scenic view mode; the steps for adjusting the parameters of the camera equipment and related vehicle cabin equipment based on the photo-taking modes include: Adjust the phone camera parameters, sunroof opening parameters, and seat angle parameters based on the shooting mode.

7. The method according to claim 1, characterized in that, After the step of capturing images using the camera device, the method further includes: Evaluate the shooting effect of the image, and determine whether there is a shooting problem based on the shooting effect; If the aforementioned shooting problem exists, generate guidance information and / or adjust the parameters of the camera equipment and related equipment in the vehicle cockpit based on the shooting problem; The image was re-captured using the camera device.

8. A vehicle cabin photography guidance device, characterized in that, The device includes: The data perception and acquisition module is used to collect data from the vehicle based on the vehicle's perception sensors; wherein, the vehicle data includes: environmental data and status data; The scene analysis and decision-making module is used to determine optimization requirements based on the vehicle's data and the photography scene. The guidance generation module is used to generate guidance information based on the optimization requirements, and to provide the guidance information through a human-computer interaction interface or voice prompts. The mode recommendation module is used to determine the shooting mode based on the optimization requirements and adjust the parameters of the camera equipment and related equipment in the vehicle cabin based on the shooting mode. An execution feedback module is used to capture images through the camera device.

9. An electronic device, characterized in that, The system includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the vehicle cockpit photography guidance method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the vehicle cockpit photography guidance method according to any one of claims 1 to 7.

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