LED digital background shooting monitoring method and device

Abstract

The application discloses an LED digital background shooting monitoring method, device and equipment. The method collects data of a whole processing link of an LED digital background shooting system, including virtual digital assets, a software running environment, upstream and downstream hardware and the like, integrates data of various modules in the LED digital background shooting system, automatically analyzes and locates problem points and potential risks on the LED digital background shooting link, realizes whole-link monitoring of the LED digital background shooting system, and thus improves problem troubleshooting efficiency of the LED digital background shooting system, and improves stability of the shooting system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of LED digital background shooting, in particular to an LED digital background shooting monitoring method and device, and an electronic device. BACKGROUND

[0002] LED digital background shooting is a shooting method that projects a video or a real-time rendered image on an LED screen as an LED digital background. An LED digital background shooting system (hereinafter referred to as a shooting system) involves multiple users, multiple devices, multiple processing links, and multiple technical processes, and has high system complexity. Therefore, a monitoring system is needed to troubleshoot problems existing in the use of the shooting system, so as to ensure the stable operation of the shooting system and support the normal development of shooting tasks.

[0003] Currently, the monitoring method is to monitor the running state of each module in the shooting system. For example, the running state of the LED screen hardware is monitored through a screen management tool; the running state of the 2D video played on the LED screen is monitored through a video broadcast control tool; the running state of the 3D digital background rendering server is monitored through a tool provided by a game engine; and the running state of the 2D video + 3D digital background shooting is monitored through a virtual shooting system.

[0004] However, in the process of implementing the present application, the inventors found that the above technical solution at least has the following problems: it does not have full-link monitoring capability, and when a problem occurs, it is difficult for the user to determine which link is problematic, and multiple parties such as virtual digital asset providers, software, and hardware service providers need to be coordinated to troubleshoot the problem, which is inefficient. SUMMARY

[0005] The present application provides an LED digital background shooting monitoring method to solve the problem that the prior art cannot discover potential risks in a system in time and has low problem troubleshooting efficiency. The present application further provides an LED digital background shooting monitoring device and an electronic device.

[0006] The present application provides an LED digital background shooting monitoring method, which comprises the following steps:

[0007] Obtaining multi-module data of an LED digital background shooting system;

[0008] According to the multi-module data, determining abnormal information and abnormal reason positioning information of the shooting system;

[0009] Displaying the abnormal information and the abnormal reason positioning information.

[0010] Optionally, the multi-module data comprises configuration data of multiple hardware devices.

[0011] The abnormal information and the abnormal reason positioning information of the shooting system are determined according to the multi-module data.

[0012] According to the configuration data and the configuration requirement information of the hardware device, hardware device information that does not meet the configuration requirement is obtained.

[0013] Optionally, the multi-module data includes running load data of a plurality of hardware devices.

[0014] The abnormal information and the abnormal reason positioning information of the shooting system are determined according to the multi-module data.

[0015] According to the running load data of the hardware device and the load threshold value, the hardware device information that is overloaded is obtained.

[0016] Abnormal information caused by overloading of the hardware device is obtained.

[0017] Optionally, the multi-module data includes output frame rate change data of a three-dimensional scene rendering module and data related to influencing factors of output frame rate of the three-dimensional scene rendering module.

[0018] The abnormal information and the abnormal reason positioning information of the shooting system are determined according to the multi-module data.

[0019] According to the output frame rate change data and the data related to the influencing factors, current factor information that causes the output frame rate to decrease is obtained.

[0020] Optionally, the data related to the influencing factors includes specification data of shooting materials and GPU hardware decoding support shooting material specification data, operation capability data of a rendering server, load data of the rendering server, frame rate of output images of each module, video memory data, GPU computing power data and read-write data required by a three-dimensional scene.

[0021] Optionally, the multi-module data includes GPU load data and / or video memory load data of a video play control module, specification data and specification requirement data of a video played by the video play control module, and specification data and specification requirement data of an LED screen.

[0022] The abnormal information and the abnormal reason positioning information of the shooting system are determined according to the multi-module data.

[0023] According to the GPU load data and / or the video memory load data, whether the video play control module has load abnormality is determined.

[0024] If the determination result is yes, according to the GPU load data and / or the display memory load data, the specification data and specification requirement data of the played video, and the specification data and specification requirement data of the LED screen, the cause positioning information causing the load abnormality is acquired.

[0025] Optionally, the multi-module data includes: specification data of output data of a plurality of software modules, and specification requirement data of input data of the plurality of software modules.

[0026] The determination of the abnormal information and the cause positioning information of the shooting system according to the multi-module data includes:

[0027] For the software modules having an upstream and downstream relationship, the incompatible software module information is acquired according to the specification data of the output data of the upstream software module and the specification requirement information of the input data of the downstream software module.

[0028] Optionally, the multi-module data includes: abnormal data generated by a hardware device.

[0029] The determination of the abnormal information and the cause positioning information of the shooting system according to the multi-module data includes:

[0030] The hardware device information having a fault is acquired according to the abnormal data.

[0031] Optionally, the method further includes:

[0032] The solution information is determined according to the cause positioning information.

[0033] The solution information is displayed.

[0034] Optionally, the method further includes:

[0035] The user feedback information for the abnormality is acquired.

[0036] The related data of the shooting system is adjusted according to the user feedback information.

[0037] Optionally, the method further includes:

[0038] The abnormal information and the cause positioning information of a plurality of shooting sites are acquired.

[0039] The improvement scheme information of the shooting system is determined according to the abnormal information and the cause positioning information of a plurality of shooting sites.

[0040] The application further provides an LED digital background shooting monitoring device, which includes: a data acquisition unit, a data processing unit, and a data display unit.

[0041] The data acquisition unit is configured to acquire multi-module data of the LED digital background shooting system; the data processing unit is configured to determine abnormal information and abnormal reason positioning information of the shooting system according to the multi-module data; and the data display unit is configured to display the abnormal information and the abnormal reason positioning information.

[0042] Optionally, the multi-module data comprises configuration data of a plurality of hardware devices.

[0043] The data processing unit is specifically configured to acquire hardware device information that does not meet configuration requirements according to the configuration data of the hardware devices and configuration requirement information.

[0044] Optionally, the multi-module data comprises running load data of a plurality of hardware devices; the data processing unit is specifically configured to acquire hardware device information that is overloaded according to the running load data of the hardware devices and a load threshold value, and acquire abnormal information caused by overloading of the hardware devices.

[0045] Optionally, the multi-module data comprises output frame rate change data of a three-dimensional scene rendering module and data related to influencing factors of output frame rate of the three-dimensional scene rendering module; the data processing unit is specifically configured to acquire current factor information that causes a decrease in output frame rate according to the output frame rate change data and the data related to the influencing factors.

[0046] Optionally, the data related to the influencing factors comprises specification data of shooting materials and shooting material specification data supported by GPU hardware decoding, operation capability data of a rendering server, load data of the rendering server, frame rates of output images of each module, and video memory data, GPU computing power data and read-write data required by a three-dimensional scene.

[0047] Optionally, the multi-module data comprises GPU load data and / or video memory load data of a video play control module, specification data and specification requirement data of a video played by the video play control module, and specification data and specification requirement data of an LED screen; the data processing unit is specifically configured to determine whether the video play control module has load abnormality according to the GPU load data and / or the video memory load data; if the determination result is yes, reason positioning information that causes the load abnormality is acquired according to the GPU load data and / or the video memory load data, the specification data and the specification requirement data of the video played by the video play control module, and the specification data and the specification requirement data of the LED screen.

[0048] Optionally, the multi-module data comprises: specification data of output data of the plurality of software modules, and specification requirement data of input data of the plurality of software modules; and the data processing unit is specifically configured to: for the software modules having an upstream and downstream relationship, acquire the incompatible software module information according to the specification data of the output data of the upstream software module and the specification requirement information of the input data of the downstream software module.

[0049] Optionally, the multi-module data comprises: abnormal data generated by the hardware device; and the data processing unit is specifically configured to: acquire the hardware device information that is malfunctioning according to the abnormal data.

[0050] Optionally, the apparatus further comprises: a solution determining unit and a solution display unit.

[0051] The solution determining unit is configured to: determine solution information according to the abnormal cause positioning information; and the solution display unit is configured to: display the solution information.

[0052] Optionally, the apparatus further comprises: a user feedback acquiring unit and a photographing system adjusting unit.

[0053] The user feedback acquiring unit is configured to: acquire user feedback information for the abnormality; and the photographing system adjusting unit is configured to: adjust related data of the photographing system according to the user feedback information.

[0054] The application further provides a computer readable storage medium, wherein instructions are stored in the computer readable storage medium, and when the instructions are executed on a computer, the computer executes the various methods.

[0055] The application further provides a computer program product comprising instructions, and when the instructions are executed on a computer, the computer executes the various methods.

[0056] Compared with the prior art, the application has the following advantages:

[0057] The LED digital background photographing monitoring method provided by the embodiment of the application collects data of a full processing link of an LED digital background photographing system, including virtual digital assets, a software running environment, upstream and downstream hardware, integrates data of each module in the LED digital background photographing system, automatically analyzes and locates problem points and potential risks on the LED digital background photographing link, and realizes full-link monitoring of the LED digital background photographing system, thereby improving problem troubleshooting efficiency of the LED digital background photographing system and improving stability of the photographing system. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 The embodiment of the LED digital background photographing monitoring method provided by the application is shown in a flowchart.

[0059] Figure 2 A schematic diagram of the shooting system of an embodiment of the LED digital background shooting monitoring method provided in this application;

[0060] Figure 3 The monitoring system structure diagram of an embodiment of the LED digital background shooting monitoring method provided in this application. Detailed Implementation

[0061] Many specific details are set forth in the following description to provide a full understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this application; therefore, this application is not limited to the specific embodiments disclosed below.

[0062] This application provides an LED digital background shooting and monitoring method and apparatus, as well as electronic equipment. The various solutions are described in detail below in each embodiment.

[0063] First Embodiment

[0064] Please refer to Figure 1 This is a flowchart of the LED digital background shooting and monitoring method of this application. In this embodiment, the method may include the following steps:

[0065] Step S101: Acquire multi-module data from the LED digital background shooting system.

[0066] The LED digital background shooting monitoring method provided in this embodiment monitors multiple modules in the shooting system, including virtual digital assets, hardware and software specifications and operating status, etc., and performs overall risk assessment of the shooting system by comprehensively monitoring the entire shooting system.

[0067] The shooting system described herein is a system for filming movies and television programs by projecting video or real-time rendered images onto an LED screen as an LED digital background. The shooting system may include complex software functions such as the creation of virtual digital assets, the presentation and real-time adjustment of digital assets, video playback control, real-time rendering of 3D scenes, camera motion capture data acquisition, and camera image acquisition and fusion. It also includes the construction and maintenance of a series of hardware devices such as various playback control and rendering servers, image data sending and receiving cards, and LED screen walls.

[0068] like Figure 2As shown, the shooting system of the embodiment can include the following modules: virtual digital assets, a broadcast control server, a camera motion compensation device, a rendering service cluster, an image processor, and an LED screen wall. The virtual digital assets, also known as shooting material data, are based on the image content presented on the LED background wall according to the shooting scene, and the forms include pictures, ultra-high-definition videos, virtual 3D scenes, etc. The LED screen wall is built by splicing small-pitch LED screen boxes and is used to present virtual digital assets. The broadcast control server is the core control unit of the shooting system and is responsible for managing digital assets, controlling the playing, pausing, real-time color adjustment of digital assets, and data transfer between different modules in the link. The camera motion compensation device is responsible for collecting data such as the spatial position, focal length, and aperture change of the camera, and the image presented by the LED screen needs to be adjusted accordingly according to these input data of the camera. The rendering service cluster is responsible for real-time rendering of digital assets, and according to the different types of digital assets, it can be divided into video decoding services and 3D virtual scene rendering servers. According to the size of the image to be presented, one or several rendering servers are needed to form a cluster to provide rendering services. The image processor is responsible for post-processing the image output by the rendering service cluster, such as segmentation, HDR10 enhancement, etc. In scenes where the output image quality does not need to be specially processed, this module can be removed. The LED screen wall is built by splicing hundreds of small LED screen boxes, and the video signal sending card and the receiving card cooperate with each other to distribute the upstream input video signal to hundreds of LED screens.

[0069] The multi-module data of the shooting system includes but is not limited to: specification data of shooting materials, specification data of software modules, specification data of hardware devices, and running state data of hardware devices.

[0070] The shooting material is also called virtual digital assets, which is based on the image content presented on the LED background wall according to the shooting scene, and the forms include pictures, ultra-high-definition videos, virtual 3D scenes, etc. The specification data of the shooting material includes but is not limited to: material size, format, etc. such as picture pixels, video frame rate, etc. The shooting material data of the embodiment is shown in Table 1 as follows:

[0071]

[0072]

[0073] Table 1, shooting material data table

[0074] The software modules include, but are not limited to: a video playback control module for playing 2D video on an LED screen, a 3D scene real-time rendering module, a camera motion capture data acquisition module, a virtual shooting module, and an image processing module. The specifications of the software modules may include the specifications for both input and output data. For example, input data specifications may include the HDMI version, maximum resolution, and frame rate supported by the sending card input, while output data specifications may include the number and specifications of the rendering server's graphics card output interfaces, the color gamut, and the format of the image data.

[0075] The hardware devices include, but are not limited to: LED screen walls, cameras, image data sending and receiving cards, and rendering servers. The configuration data of the hardware devices refers to their technical specifications, such as the color gamut, bit depth, and service life supported by the LED screen. The operational status data of the hardware devices includes, but is not limited to, the load on the hardware devices during operation, such as the GPU load and video memory load of each computing server, and may also include memory usage and local area network packet loss rate.

[0076] like Figure 3 As shown, monitoring tools deployed on the client side at the shooting location can be used to acquire data from various modules of the shooting system. In this embodiment, the client-side monitoring tools include: a virtual digital asset analysis tool, a computing server monitoring tool, and an LED screen monitoring tool. The virtual digital asset analysis tool is used to acquire the shooting material data from the virtual digital asset processing module. The computing server monitoring tool is used to acquire relevant software module data and hardware device data from the broadcast control server, rendering server cluster, and image processor. The LED screen monitoring tool can be used to acquire data related to the video signal transmission card.

[0077] In practice, the computing server monitoring tool can call upon existing monitoring tools for each module to obtain data for that module. For example, it can obtain software specifications data for 2D video playback software, technical indicators and operating load data for the broadcast control server through video broadcast control tools; obtain specifications data for 3D digital background rendering software, technical indicators and operating load data for the rendering service cluster through tools provided by the game engine; and obtain specifications data for 2D video + 3D digital background shooting software, technical indicators and operating load data for the image processor through the virtual shooting system.

[0078] Step S103: Based on the multi-module data, determine the abnormal information and the location information of the abnormal cause of the shooting system.

[0079] like Figure 3As shown, the client monitoring tool reports the collected multi-module data to the data analysis server. The server can be deployed in the cloud or on a server within the local area network of the shooting system. The data analysis service is responsible for analyzing all the collected data, identifying problems or risks in the shooting system, and issuing alarms.

[0080] In one example, the multi-module data includes configuration data for multiple hardware devices. Step S103 can be implemented as follows: based on the configuration data and configuration requirement information of the hardware devices, information on hardware devices that do not meet the configuration requirements is obtained. For example, the configuration requirement for an LED screen wall is that the spacing between LED screens is greater than 3 millimeters. Using this processing method, hardware devices whose hardware specifications do not meet the requirements for LED digital background shooting can be identified, and users can adjust the hardware configuration based on this information.

[0081] In one example, the multi-module data includes: operating load data of multiple hardware devices; step S103 can be implemented as follows: based on the operating load data and load threshold of the hardware devices, obtain information on overloaded hardware devices; obtain abnormal information caused by hardware device overload. For example, excessive GPU load on the rendering server leads to a decrease in the output frame rate. This processing method allows for timely detection of the risk of decreased output frame rate in real-time rendering of 3D scenes, and identifies the cause as excessive GPU load on the rendering server. This allows users to intervene in the GPU load in a timely manner, avoiding image stuttering caused by a continuous decrease in the output frame rate.

[0082] In one example, the multi-module data includes: GPU load data and / or video memory load data of the video playback control module, specification data and specification requirements data of the video being played by the video playback control module, and specification data and specification requirements data of the LED screen. Step S103 can be implemented as follows: based on the GPU load data and / or video memory load data, determine whether the video playback control module is experiencing load anomalies; if the determination result is yes, then based on the GPU load data and / or video memory load data, and the specification data and specification requirements data of the video being played, and the specification data and specification requirements data of the LED screen, obtain the cause location information of the load anomaly. This processing method allows for the identification of whether the GPU load or video memory load anomalies occur during video playback control due to upstream digital asset issues or downstream screen hardware issues.

[0083] In one example, the multi-module data includes: specification data of output data from multiple software modules, and specification requirement data of input data from multiple software modules. Step S103 can be implemented as follows: For software modules with upstream and downstream relationships, based on the specification data of output data from the upstream software module and the specification requirement information of input data from the downstream software module, information on incompatible software modules is obtained. This processing method can identify incompatibility issues between upstream and downstream modules in the shooting system. For example, the rendering server outputs 4K@60 frames 10-bit YUV data, but the image processor supports a maximum input of 4K@30 frames 8-bit RGB data; therefore, it can be determined that the rendering server and the image processor are incompatible.

[0084] In one example, the multi-module data includes: abnormal data generated by hardware devices, such as when an individual LED cabinet experiences a short circuit leading to a temperature increase, the LED screen will report a temperature abnormality; step S103 can be implemented as follows: based on the abnormal data, obtain information about the faulty hardware device, such as an abnormality reported by a hardware module during operation, such as a short circuit in an individual LED cabinet causing a temperature increase. This processing method can promptly detect faulty devices, allowing users to handle equipment malfunctions in a timely manner and ensuring the normal operation of the shooting system.

[0085] In one example, the multi-module data includes: output frame rate change data of the 3D scene rendering module, and data related to factors affecting the output frame rate of the 3D scene rendering module. Step S103 can be implemented as follows: based on the output frame rate change data and the data related to the influencing factors, obtain information on the current factors causing the decrease in output frame rate. For example, during operation, the output frame rate of real-time rendering of the 3D scene is affected by multiple factors, such as the GPU load of the rendering server and the specifications of the 3D scene data. When the monitoring system detects a continuous decrease in output frame rate, it can detect data related to each factor to identify the current factor causing the problem, such as the high GPU load of the rendering server or other factors. Using this processing method, it is possible to detect whether there is a risk of a decrease in the output frame rate of real-time rendering of the 3D scene in the shooting system, and the current cause of the risk. Users can adjust the shooting system according to the specific cause to eliminate the risk, avoid LED digital background image stuttering problems, and ensure the normal operation of the shooting system.

[0086] The data related to the influencing factors include, but are not limited to, at least one of the following: the specifications of the shooting material and the specifications of the shooting material supported by GPU hardware decoding, the computing power data of the rendering server, the load data of the rendering server, the frame rate of the output images of each module, and the video memory data, GPU computing power data, and read / write data required for the 3D scene.

[0087] Taking LED digital background image stuttering as an example, the LED digital background shooting monitoring system can detect and alarm in advance when the frame rate of the LED digital background drops. By analyzing the digital asset specifications, the theoretical computing power of the rendering server, the actual load of the rendering server, and the image output frame rate of each module, the monitoring system can clearly locate the cause of the LED digital background frame rate drop.

[0088] Step S105: Display the abnormal information and the location information of the abnormal cause.

[0089] In this embodiment, an LED digital background shooting scheme was used for filming car chase scenes. The LED digital background used projected video to simulate the street scene receding during vehicle movement. However, the LED digital background image experienced stuttering. Troubleshooting and locating this problem requires analysis and investigation of multiple aspects, including virtual digital assets, broadcast control software, the broadcast control software operating environment, and hardware specifications. Specifically, this includes:

[0090] 1. For digital assets, first confirm the refresh rate during digital asset acquisition to ensure it meets specifications and whether there are duplicate frames. Second, confirm the size of the digital assets to check if the large size of the digital assets is causing read / write operations to become a bottleneck, leading to reduced processing power. Third, confirm whether the encoding specifications of the digital assets match the GPU's decoding capabilities and whether they are on the GPU's supported list.

[0091] 2. For the broadcast control software, first confirm whether the broadcast control software uses the most efficient GPU decoding, and secondly confirm whether the output frame rate of the broadcast control software is lower than expected.

[0092] 3. Check the broadcast control software's operating environment: whether key resources such as CPU load, GPU rendering load, GPU decoding load, system memory, and system video memory have reached bottlenecks; whether overheat protection mechanisms have reduced processing power; and whether other background processes are consuming too many system resources.

[0093] 4. Hardware specifications: First, confirm the highest resolution and refresh rate supported by the graphics card output signal. Is the highest frame rate that can be output at the current resolution limited by the graphics card output specifications? Second, confirm the highest resolution and refresh rate supported by the sending card, receiving card, and LED screen. Is the highest frame rate that can be output at the current resolution limited by the hardware input and output specifications?

[0094] This practical problem demonstrates that, due to the high complexity of the shooting system, there are many factors that can cause image stuttering. The monitoring method provided in this application can automatically identify image stuttering problems in the shooting system, automatically locate the various factors that cause the problem, and display them to the user.

[0095] In one example, the method may further include the following steps: determining solution information based on the anomaly cause location information; and displaying the solution information. This approach can recommend appropriate solutions to users, facilitating quick problem-solving and ensuring the normal operation of the shooting system. For example, if the specifications of video digital assets are not on the GPU hardware decoding support list, the user can be recommended to transcode the digital assets to the recommended specifications; if the 3D scene is too complex and exceeds the rendering server's capabilities, the specific resource bottleneck can be analyzed—whether it's video memory, GPU computing power, or read / write operations—and the user can be recommended to expand the corresponding resources.

[0096] In one example, the method may further include the following steps: obtaining user feedback information regarding the anomaly; and adjusting relevant data of the shooting system based on the user feedback information. This approach allows problems to be resolved through the monitoring system, eliminating the need for users to address each module independently, thus effectively improving problem-solving efficiency.

[0097] In one example, the method may further include the following steps: acquiring the anomaly information and anomaly cause location information from multiple shooting locations; and determining the improvement scheme information for the shooting system based on the anomaly information and anomaly cause location information from multiple shooting locations. For example, analyzing all video playback stuttering incidents, it was found that 60% of the stuttering incidents occurred because users had enabled the blurring post-processing. Therefore, it was inferred that blurring post-processing consumes a significant amount of system resources, leading to stuttering. Subsequently, the implementation of blurring post-processing was optimized to reduce the system resources consumed by blurring post-processing, greatly reducing stuttering incidents during video playback.

[0098] As can be seen from the above embodiments, the LED digital background shooting monitoring method provided in this application collects data from the entire processing chain of the LED digital background shooting system, including virtual digital assets, software operating environment, upstream and downstream hardware, etc., integrates the data of each module in the LED digital background shooting system, automatically analyzes and locates the problem points and potential risks in the LED digital background shooting chain, and realizes full-chain monitoring of the LED digital background shooting system. This can improve the efficiency of problem investigation in the LED digital background shooting system, thereby enhancing the stability of the shooting system.

[0099] Second Embodiment

[0100] In the above embodiments, an LED digital background shooting monitoring method is provided. Correspondingly, this application also provides an LED digital background shooting monitoring device. This device corresponds to the embodiments of the above method. Since the device embodiments are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. The device embodiments described below are merely illustrative.

[0101] This application also provides an LED digital background shooting and monitoring device, including: a data acquisition unit, a data processing unit, and a data display unit.

[0102] The data acquisition unit is used to acquire multi-module data from the LED digital background shooting system; the data processing unit is used to determine the abnormal information and the location information of the abnormal cause of the shooting system based on the multi-module data; and the data display unit is used to display the abnormal information and the location information of the abnormal cause.

[0103] Optionally, the multi-module data includes: configuration data of multiple hardware devices;

[0104] The data processing unit is specifically used to obtain information about hardware devices that do not meet the configuration requirements based on the configuration data and configuration requirement information of the hardware devices.

[0105] Optionally, the multi-module data includes: operating load data of multiple hardware devices; the data processing unit is specifically used to obtain overloaded hardware device information based on the operating load data and load threshold of the hardware devices; and to obtain abnormal information caused by hardware device overload.

[0106] Optionally, the multi-module data includes: output frame rate change data of the 3D scene rendering module, and data related to factors affecting the output frame rate of the 3D scene rendering module; the data processing unit is specifically used to obtain current factor information causing the output frame rate to decrease based on the output frame rate change data and the data related to the influencing factors.

[0107] Optionally, the data related to the influencing factors include: the specifications of the shooting material and the specifications of the shooting material supported by GPU hardware decoding, the computing power data of the rendering server, the load data of the rendering server, the frame rate of the output images of each module, and the video memory data, GPU computing power data, and read / write data required for the 3D scene.

[0108] Optionally, the multi-module data includes: GPU load data and / or video memory load data of the video playback control module, specification data and specification requirements data of the video played by the video playback control module, and specification data and specification requirements data of the LED screen; the data processing unit is specifically used to determine whether the video playback control module has an abnormal load based on the GPU load data and / or video memory load data; if the above determination result is yes, then based on the GPU load data and / or video memory load data, and the specification data and specification requirements data of the video played, and the specification data and specification requirements data of the LED screen, the cause location information of the abnormal load is obtained.

[0109] Optionally, the multi-module data includes: specification data of output data from multiple software modules, and specification requirement data of input data from multiple software modules; the data processing unit is specifically used to obtain incompatible software module information for software modules with upstream and downstream relationships, based on the specification data of output data from upstream software modules and the specification requirement information of input data from downstream software modules.

[0110] Optionally, the multi-module data includes: abnormal data generated by the hardware device; the data processing unit is specifically used to obtain information about the faulty hardware device based on the abnormal data.

[0111] Optionally, the device may further include: a solution determination unit and a solution display unit.

[0112] The solution determination unit is used to determine solution information based on the anomaly cause location information; the solution display unit is used to display the solution information.

[0113] Optionally, the device may further include: a user feedback acquisition unit and a shooting system adjustment unit.

[0114] The user feedback acquisition unit is used to acquire user feedback information regarding anomalies; the shooting system adjustment unit is used to adjust relevant data of the shooting system based on the user feedback information.

[0115] Third Embodiment

[0116] In the above embodiments, an LED digital background shooting and monitoring method is provided. Correspondingly, this application also provides an electronic device. This device corresponds to the embodiments of the above method. Since the device embodiments are basically similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments. The device embodiments described below are merely illustrative.

[0117] The electronic device in this embodiment includes:

[0118] Processor and memory;

[0119] The memory stores the program for implementing the LED digital background shooting and monitoring method described above. The device is powered on and the program of the method is run by the processor.

[0120] Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

[0121] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0122] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0123] 1. Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0124] 2. Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

Claims

1. A method for monitoring LED digital background shooting, characterized in that, include: Acquire multi-module data from the entire processing chain of the LED screen wall digital background shooting system. The LED screen wall consists of multiple LED screens, and the multi-modules in the entire processing chain have upstream and downstream relationships. The entire processing chain includes: a module for creating shooting materials, including virtual 3D scenes; a broadcast control server for managing shooting materials, controlling the playback of shooting materials on the LED screen wall, and data transfer between different modules in the chain; a rendering service cluster for rendering shooting materials in real time on the LED screen wall, including a 3D scene rendering module; a camera for shooting against the background of the shooting materials displayed on the LED screen wall; a camera motion capture data acquisition module deployed on the camera motion capture device side; a camera image acquisition and fusion module; an image processing module; an image processor; an image data sending card; and an image data receiving card; the multi-module data includes: output frame rate change data of the 3D scene rendering module; and data related to factors affecting the output frame rate of the 3D scene rendering module; the data related to factors affecting the output frame rate includes at least one of the following: specification data of the shooting materials and specification data of the shooting materials supported by GPU hardware decoding; computing power data of the rendering server; load data of the rendering server; frame rate of the output images of each module; and video memory data, GPU computing power data, and read / write data required by the 3D scene; Based on the multi-module data, determine the abnormal information and abnormal cause location information of the shooting system, including: based on the output frame rate change data and the data related to the influencing factors, obtain the current factor information that causes the output frame rate to drop; Display the anomaly information and the anomaly cause location information. The anomaly cause includes at least one of the following: incompatibility between upstream and downstream modules, or abnormal load of upstream and downstream modules.

2. The method according to claim 1, characterized in that, The multi-module data includes: configuration data of multiple hardware devices; The step of determining the abnormal information and abnormal cause location information of the shooting system based on the multi-module data includes: Based on the configuration data and configuration requirement information of the hardware device, obtain information on hardware devices that do not meet the configuration requirements.

3. The method according to claim 1, characterized in that, The multi-module data includes: the operating load data of multiple hardware devices; The step of determining the abnormal information and abnormal cause location information of the shooting system based on the multi-module data includes: Based on the operating load data and load threshold of the hardware device, obtain information about the overloaded hardware device; Obtain abnormal information caused by hardware device overload.

4. The method according to claim 1, characterized in that, The multi-module data includes: GPU load data and / or video memory load data of the video playback control module, specification data and specification requirements data of the video played by the video playback control module, and specification data and specification requirements data of the LED screen. The step of determining the abnormal information and abnormal cause location information of the shooting system based on the multi-module data includes: Based on the GPU load data and / or video memory load data, determine whether the video playback control module is experiencing load anomalies; If the above judgment result is yes, then based on the GPU load data and / or video memory load data, the specification data and specification requirements data of the video being played, and the specification data and specification requirements data of the LED screen, the cause location information of the abnormal load is obtained.

5. The method according to claim 1, characterized in that, The multi-module data includes: specification data of output data from multiple software modules, and specification requirement data of input data from multiple software modules. The step of determining the abnormal information and abnormal cause location information of the shooting system based on the multi-module data includes: For software modules with upstream and downstream relationships, information on incompatible software modules is obtained based on the specification data of the output data of the upstream software module and the specification requirements of the input data of the downstream software module.

6. The method according to claim 1, characterized in that, The multi-module data includes: abnormal data generated by hardware devices; The step of determining the abnormal information and abnormal cause location information of the shooting system based on the multi-module data includes: Based on the abnormal data, obtain information about the faulty hardware device.

7. The method according to claim 1, characterized in that, Also includes: Based on the anomaly cause location information, determine the solution information; Showcase solution information.

8. The method according to claim 1 or 4, characterized in that, Also includes: Obtain user feedback information regarding the anomalies; Based on the user feedback, adjust the relevant data of the shooting system.

9. An LED digital background shooting and monitoring device, characterized in that, include: The data acquisition unit is used to acquire multi-module data of the entire processing link of the LED screen wall digital background shooting system. The LED screen wall includes multiple LED screens, and the multi-modules of the entire processing link have upstream and downstream relationships. The entire processing chain includes: a module for creating shooting materials, including virtual 3D scenes; a broadcast control server for managing shooting materials, controlling the playback of shooting materials on the LED screen wall, and data transfer between different modules in the chain; a rendering service cluster for rendering shooting materials in real time on the LED screen wall, including a 3D scene rendering module; a camera for shooting against the background of the shooting materials displayed on the LED screen wall; a camera motion capture data acquisition module deployed on the camera motion capture device side; a camera image acquisition and fusion module; an image processing module; an image processor; an image data sending card; and an image data receiving card; the multi-module data includes: output frame rate change data of the 3D scene rendering module; and data related to factors affecting the output frame rate of the 3D scene rendering module; the data related to factors affecting the output frame rate includes at least one of the following: specification data of the shooting materials and specification data of the shooting materials supported by GPU hardware decoding; computing power data of the rendering server; load data of the rendering server; frame rate of the output images of each module; and video memory data, GPU computing power data, and read / write data required by the 3D scene; The data processing unit is used to determine the abnormal information and abnormal cause location information of the shooting system based on the multi-module data, including: obtaining the current factor information that causes the output frame rate to drop based on the output frame rate change data and the data related to the influencing factors; The data display unit is used to display the abnormal information and the location information of the abnormal cause. The abnormal cause includes at least one of the following: incompatibility between upstream and downstream modules, or abnormal load of upstream and downstream modules.

10. An electronic device, characterized in that, include: Processor and memory; A memory for storing a program for implementing the method of any one of claims 1-8, wherein the device is powered on and the program of the method is executed by the processor.

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