Intelligent photostudio light control system and AI processing method

Abstract

The invention relates to the technical field of image processing and intelligent control, and discloses an intelligent photostudio light control system and an AI processing method, and the system comprises at least one camera module which is used for collecting an image of a photographed object; the light module is provided with a main light source, a contour light source and a background light source; the environment sensing module is used for detecting illumination parameters in a shooting environment; the control module is used for controlling the illumination intensity and the color temperature of the light module according to the parameters collected by the environment sensing module; and the AI processing terminal is used for receiving the image or video data acquired by the camera module. By introducing environment perception and intelligent control, linkage control of automatic light adjustment and multi-angle image acquisition in the shooting process is realized, and automation and consistency of image acquisition are improved; and in combination with a cloud AI image processing and copywriting generation module, the system can complete shooting, processing and finished product output by one key, so that the content production process is obviously optimized, and the operation threshold is reduced.

Description

Technical Field

[0001] The present invention relates to the technical fields of image processing and intelligent control, and specifically to an intelligent photography studio lighting control system and an AI processing method. Background Art

[0002] With the rapid development of e-commerce, short video marketing, and social media content industries, the quality of product images and video content has become a key factor affecting users' purchase decisions and dissemination efficiency. To enhance visual expression effects, more and more content production scenarios have begun to rely on professional photography studio equipment, including multi-light-position lighting systems, rotating platforms, multi-camera shooting architectures, and image post-processing tools. However, in actual operation, existing photography systems usually have problems such as fragmented processes, complex operations, and reliance on manual experience, and are difficult to meet the requirements of fast, diverse, and high-frequency content production.

[0003] Current photography studio systems generally adopt the methods of manually adjusting lights, manually configuring angles, and uploading post-processing step by step. This method not only requires high professional experience of operators, but also is difficult to guarantee in terms of lighting consistency, shooting efficiency, and post-production finished product standardization. Once the surface material of the product or the shooting environment changes, the lighting layout and shooting parameters often need to be reset, increasing labor costs and error probabilities. In addition, content such as post-image matte extraction, color correction, and copywriting generation still needs to be manually completed with the help of multiple software. The processing process is fragmented and inefficient, lacking an end-to-end automation mechanism.

[0004] On the other hand, although artificial intelligence technology has made great progress in the fields of image recognition, image generation, and natural language processing, it has not been systematically integrated into the photography studio scenario. Especially between image acquisition, environmental response control, and AI intelligent processing, there is a lack of a highly integrated and linked intelligent control mechanism. Therefore, there is an urgent need for a photography system with intelligent perception, automatic control, and AI processing capabilities, which can complete the whole process from shooting preparation, image acquisition to content generation without manual intervention, and improve content production efficiency, quality, and consistency. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides an intelligent photography studio lighting control system and an AI processing method, which solve the problems of low automation degree, strong operation dependence, and low processing efficiency in the lighting control, multi-angle shooting, and post-processing processes of existing photography studio systems.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent photography studio lighting control system and an AI processing method, including:

[0007] At least one camera module for collecting images of the object to be photographed;

[0008] A lighting module, which is provided with a main light source, a contour light source and a background light source;

[0009] An environment perception module, which is used to detect the lighting parameters in the shooting environment;

[0010] A control module, which is used to control the light intensity and color temperature of the lighting module according to the parameters collected by the environment perception module;

[0011] An AI processing terminal, which is used to receive the image or video data collected by the camera module, and perform image matting, color adjustment, image restoration, video editing or copywriting generation processing on the data based on an AI model;

[0012] A user interaction module, which is used to receive the task settings of the user and transmit back the finished content after AI processing.

[0013] Preferably, the camera module includes multiple cameras, which are used for all-round shooting without dead angles.

[0014] Preferably, the lighting module performs dynamic adjustment of brightness and color temperature in a PWM manner.

[0015] Preferably, the control module dynamically generates light adjustment parameters based on the product material recognition algorithm and the ambient light detection result, and controls the lighting module to output the corresponding brightness and color temperature.

[0016] Preferably, the system further includes a rotating platform module, which is used to carry the object to be photographed and perform controllable angle rotation to achieve multi-angle shooting.

[0017] Preferably, the AI processing terminal includes:

[0018] An image processing module, which is used to perform image matting of the U-Net model and image restoration of the GAN model;

[0019] A color processing module, which performs style matching and color adjustment based on the CLIP model;

[0020] A video processing module, which uses FFmpeg to perform editing and synthesis on the image sequence;

[0021] A copywriting generation module, which generates product description text based on a natural language model.

[0022] Preferably, the AI processing terminal is set in a cloud server, and performs data communication with the control module and the user interaction module through a network.

[0023] Preferably, the user interaction module includes a mobile terminal application (APP), which is used to set the shooting mode, lighting scheme, visual style, and receive the image, video and copywriting results after AI processing.

[0024] Preferably, the system supports the invocation of multiple preset shooting modes, including but not limited to the e-commerce main picture mode, the short video mode, and the multilingual subtitle generation mode.

[0025] An intelligent studio lighting control method includes the following steps:

[0026] 1) The user sets the shooting task parameters through an interactive terminal;

[0027] 2) Collect ambient light information and product image information;

[0028] 3) Automatically adjust the brightness and color temperature of the lighting module based on the ambient information and the product material recognition result;

[0029] 4) Collect product image or video materials through a multi-angle camera;

[0030] 5) Upload the collected data to the AI processing terminal to perform image matting, color correction, image restoration, video editing, and copywriting generation;

[0031] 6) Synchronously backhaul the finished content to the user terminal.

[0032] The present invention provides an intelligent studio lighting control system and an AI processing method. It has the following beneficial effects:

[0033] 1. By integrating the environmental perception module and the lighting control module, the present invention realizes the real-time perception and dynamic adjustment of the lighting environment in the studio, and can automatically match the lighting intensity and color temperature according to the material type of the object to be photographed and the current ambient light state, thereby effectively solving the problem of inconsistent light and shadow caused by inaccurate manual light adjustment in traditional shooting, and ensuring a high degree of consistency in the light effect performance of multi-batch and cross-scene shooting content.

[0034] 2. The present invention adopts a multi-camera layout combined with a rotating platform control technology, which supports image or video acquisition of the object to be photographed from multiple angles, enhancing the three-dimensional sense and information coverage of the image. This multi-angle data acquisition mechanism provides a more comprehensive material basis for subsequent AI modeling, image synthesis, and display, and solves the technical problem of single static shooting angle and limited visual expression in traditional shooting.

[0035] 3. The present invention embeds the AI model into the automated workflow to realize the intelligent processing of images and videos after shooting. Through the cloud AI processing terminal, users can obtain finished materials that meet the preset style and platform requirements without the need to have the ability to operate post-production software, significantly optimizing the image processing link and reducing the technical threshold of content production.

[0036] 4. The present invention supports calling a natural language model for automatic copywriting generation after image processing is completed, and outputs text content including product descriptions, promotional terms, titles, or tags, etc., to meet the requirements of multiple content publishing scenarios. Through the linkage between pictures and texts and semantic matching, the invention solves the problem of the separation of shooting and copywriting and the need for manual intervention, and forms a more complete content production closed loop. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Please refer to the attached Figure 1 , the embodiments of the present invention provide an intelligent studio lighting control system, including:

[0040] At least one camera module for collecting images of the object to be photographed;

[0041] The camera module is used to collect multi-angle images of the object to be photographed. Preferably, the present invention uses multiple high-definition cameras, and multiple cameras work simultaneously, and the image data is synchronously transmitted to the control module.

[0042] To ensure clear and stable imaging, the camera has the following configurations:

[0043] The resolution is not less than 1080p;

[0044] Supports fixed focal length or autofocus;

[0045] Supports local HDR optimization processing.

[0046] A lighting module, provided with a main light source, a contour light source, and a background light source;

[0047] The lighting module includes:

[0048] The main light source (front direction);

[0049] The contour light source (side-rear direction);

[0050] The background light source (background curtain direction);

[0051] All light sources adopt adjustable LED lamp groups, supporting PWM (pulse width modulation) control to adjust the brightness and color temperature.

[0052] Each group of light sources is controlled by an independent drive controller, and the control signals are dynamically generated by the main control module. Each light source can be turned on separately or used in combination according to the scene requirements to simulate different environmental effects (such as soft light, contour enhancement, background blurring, etc.).

[0053] An environmental perception module for detecting the lighting parameters in the shooting environment;

[0054] The environmental perception module is equipped with multiple lighting sensors (such as photodiodes, digital color temperature sensors, etc.) for real-time collection of the lighting intensity (unit: Lux) and color temperature (unit: K) in the environment.

[0055] The data collected is used by the main control module to evaluate the current ambient light conditions and, in combination with the material type of the shooting object, automatically derive the optimal lighting configuration parameters.

[0056] The collection period of this module can be configured from 500ms to 2s to ensure the real-time nature of the response.

[0057] A control module for controlling the lighting intensity and color temperature of the lighting module according to the parameters collected by the environmental perception module;

[0058] The control module is the brain of the system, used to receive the settings of the user side and coordinate the collaborative operation of the sub-modules.

[0059] It is internally integrated with:

[0060] MCU (Micro Control Unit) or an embedded computing platform (such as RaspberryPi);

[0061] Data synchronization interfaces (such as USB, UART, I2C);

[0062] Local cache storage module (such as SD card);

[0063] The control module receives the environmental perception data and, in combination with the task settings, automatically generates the following control instructions:

[0064] Lighting brightness / color temperature setting;

[0065] Camera startup / shutter synchronization;

[0066] Rotation angle / time of the rotating platform;

[0067] After shooting, the data is packaged and uploaded to the AI module.

[0068] An AI processing terminal for receiving the image or video data collected by the camera module and performing image matting, color adjustment, image restoration, video editing or copywriting generation processing on this data based on the AI model;

[0069] The AI processing terminal is set up on the cloud server, receives the uploaded image / video data, and executes the following processing flow:

[0070] (1) Image processing:

[0071] Matting: Accurately segment the foreground object based on the U-Net neural network structure;

[0072] Color adjustment: Introduce the CLIP model or preset color style templates for style transfer and color matching;

[0073] Image restoration: Combine the GAN model to repair edge details and remove background noise.

[0074] (2) Video processing:

[0075] Synthesize the image sequence into a video;

[0076] Add title and ending credits;

[0077] Optionally, add automatic voiceovers and subtitles (such as generating subtitles by recognizing speech through the Whisper model).

[0078] (3) Copywriting generation:

[0079] The user provides product keywords;

[0080] The system calls a natural language model (such as GPT-4) to automatically generate copywriting that is scene-based and adapted to the platform style;

[0081] Multiple language versions are supported (such as English, Japanese, etc.).

[0082] All processing results are stored on the server and transmitted back to the user terminal through the API interface.

[0083] The user interaction module is used to receive the user's task settings and transmit back the finished content processed by the AI;

[0084] This module is preferably a mobile APP or a web-based control panel, and its functions include:

[0085] Set shooting tasks (such as "e-commerce main image", "video short film");

[0086] Select the visual style (such as "natural light", "high contrast", "portrait soft focus");

[0087] Set the output format of the finished product (such as image size, video resolution, copywriting language);

[0088] View the shooting preview in real time;

[0089] Download the finished image, video, and copywriting content.

[0090] The user interaction module communicates with the control module and the AI processing terminal via the network. The HTTPS interface or Socket protocol can be used to ensure the security of data transmission.

[0091] An intelligent photography studio lighting control method includes the following steps:

[0092] 1) The user sets the shooting task parameters through the interaction terminal;

[0093] This step is completed through the mobile APP or Web platform. The user can set the following content:

[0094] Shooting mode (such as "product main image", "360° display", "short video shooting", etc.);

[0095] Target image style (such as natural light sense, cold tone, high contrast);

[0096] Output content type (whether it includes video, whether to automatically generate copywriting);

[0097] Whether to enable rotating shooting (after enabling, the platform automatically rotates at the set angle);

[0098] Technical parameters such as file format, image size, video frame rate, etc.;

[0099] These settings are completed through the graphical interface and finally uploaded to the control module in the form of structured data (such as JSON).

[0100] 2) Collect environmental light information and product image information;

[0101] This step involves two sub-processes that are executed synchronously:

[0102] Light information collection: The environmental brightness (unit: Lux) and color temperature (unit: Kelvin) in the current photography studio are collected in real time through the light and color temperature sensors in the environmental perception module;

[0103] Initial image collection: The control module drives the camera to take a test image for subsequent judgment of material or morphological characteristics;

[0104] The collected data is used to decide on subsequent lighting adjustment strategies to adapt to the lighting methods required for different objects to be photographed (such as highly reflective metals, matte plastics, glass, etc.).

[0105] 3) Automatically adjust the brightness and color temperature of the lighting module based on the environmental information and the product material recognition result;

[0106] After receiving the data in step 2, the control module executes the following process:

[0107] Determine whether the current light intensity meets the set threshold (e.g., enable the main light when it is less than 1000 Lux);

[0108] Invoke the product recognition algorithm (e.g., use the initial image for surface material classification);

[0109] Select the appropriate combination of lighting parameters according to the preset rule library;

[0110] For example, for a metal surface → increase the contour light;

[0111] For glass material → reduce the background light to prevent reflection;

[0112] Invoke the PWM control interface to control the brightness duty cycle and color temperature adjustment of the LED lamp (control the color light ratio through a dual-color temperature chip);

[0113] After the lighting parameter adjustment is completed, an image acquisition can be performed again to verify whether the result meets the set goal.

[0114] 4) Collect product images or video materials through a multi-angle camera;

[0115] After the lighting conditions are ready, the control module starts the image acquisition process:

[0116] The three cameras take images of each angle in sequence or simultaneously (front view, top view, oblique view);

[0117] If rotational shooting is enabled in the task settings, the rotation platform drives the product to rotate at different angles (e.g., one frame every 45°), and a shot is taken when it is stationary at each angle;

[0118] All the captured materials are stored in the local cache or directly packaged and uploaded with numbers and angle markings;

[0119] The system supports shooting image sequences or continuous video streams to meet different content requirements.

[0120] 5) Upload the collected data to the AI processing terminal to perform image matting, color correction, image restoration, video editing, and copywriting generation;

[0121] The image and related metadata are uploaded to the cloud AI platform, and the processing flow is as follows:

[0122] Image matting: Invoke a deep learning algorithm based on the U-Net or ViT model to accurately segment the foreground target;

[0123] Style color correction: Combine the user-set style and invoke the CLIP or other contrastive learning models for color style transfer;

[0124] Image restoration: Apply the GAN or inpainting model to repair the target edge or background residual area;

[0125] Video editing (if enabled): combine image sequences into a video, insert opening / ending credits, and transition animations;

[0126] Copy generation (if enabled): Based on the keywords provided by the user, the natural language generation model (such as GPT) is called to generate product introduction copy, instructions for use, etc.

[0127] All finished product results are archived and stored according to a unified task number, waiting to be sent back.

[0128] 6) Synchronously transmit the finished product content back to the user terminal;

[0129] After the AI ​​platform completes the processing, the system automatically transmits the following content back through the network:

[0130] Image files (such as .jpg, .png);

[0131] Video file (such as .mp4, with .srt file when subtitles are included);

[0132] Copy content (such as .txt or .json format);

[0133] Users can view, preview and download the above content in real time through the APP interface, and can also set whether to automatically synchronize to a designated cloud disk or material library.

[0134] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Intelligent photography studio lighting control system, characterized in that, include: At least one camera module for acquiring an image of a photographed object; The lighting module is provided with a main light source, a contour light source and a background light source; Environmental perception module, used to detect lighting parameters in the shooting environment; A control module, used to control the illumination intensity and color temperature of the lighting module according to the parameters collected by the environment perception module; An AI processing terminal is used to receive the image or video data collected by the camera module, and perform image cutout, color adjustment, image restoration, video editing or text generation processing on the data based on the AI ​​model; The user interaction module is used to receive the user's task settings and return the finished content after AI processing.

2. The intelligent photography studio lighting control system according to claim 1, wherein The camera module includes multiple cameras for all-round shooting without blind spots.

3. The intelligent photography studio lighting control system according to claim 1, wherein The lighting module dynamically adjusts the brightness and color temperature through PWM.

4. The intelligent photography studio lighting control system according to claim 1, wherein The control module dynamically generates lighting adjustment parameters based on the product material recognition algorithm and the ambient light detection result, and controls the lighting module to output corresponding brightness and color temperature.

5. The intelligent photography studio lighting control system according to claim 1, characterized in that, The system further comprises a rotating platform module, which is used to carry the photographed object and rotate it at a controllable angle to achieve multi-viewing angle photography.

6. The intelligent photography studio lighting control system according to claim 1, characterized in that, The AI ​​processing terminal includes: Image processing module, used to perform image matting of U-Net model and image restoration of GAN model; Color processing module, which performs style matching and color adjustment based on the CLIP model; The video processing module uses FFmpeg to edit and synthesize image sequences; The copywriting generation module generates product description text based on the natural language model.

7. The intelligent photography studio lighting control system method according to claim 1, characterized in that The AI ​​processing terminal is located in the cloud server and performs data communication with the control module and the user interaction module through the network.

8. The intelligent photography studio lighting control system according to claim 1, wherein The user interaction module includes a mobile terminal application (APP) for setting shooting mode, lighting scheme, visual style, and receiving AI-processed images, videos and text results.

9. The intelligent photography studio lighting control system according to claim 1, wherein The system supports calling multiple preset shooting modes, including but not limited to e-commerce main picture mode, short video mode and multi-language subtitle generation mode.

10. A method for controlling the lighting of an intelligent photography studio, which is used for the intelligent photography studio lighting control system according to claims 1-9, characterized in that, The steps include: 1) The user sets the shooting task parameters through the interactive terminal; 2) Collect environmental lighting information and product image information; 3) Automatically adjust the brightness and color temperature of the lighting module based on environmental information and product material recognition results; 4) Collect product images or video materials through multi-angle cameras; 5) Upload the collected data to the AI ​​processing terminal to perform image cutout, color adjustment, image restoration, video editing and text generation; 6) Synchronously transmit the finished content back to the user terminal.

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