Method for optimizing path tracking pre-calculation based on material parameter technology

Abstract

The invention discloses a method for optimizing path tracking pre-calculation based on a material parameter technology. According to the method, the rendering efficiency and the image quality are both improved, and meanwhile, higher system flexibility and user friendliness are provided. Due to the technical effects, the method has important application value and competitive advantages in the off-line rendering industry. According to the method, the rendering efficiency and the image quality are improved, and an efficient, simple, convenient and reliable off-line rendering solution is provided for a user through intelligent management and optimization.

Description

Technical Field

[0001] The present invention relates to the field of rendering technology, and in particular to a method for optimizing path tracing pre-calculation based on material parameter technology. Background Art

[0002] In the field of 3D computer graphics, path tracing is an advanced rendering method that simulates the propagation of light in a scene, including reflection, refraction, and scattering, to generate highly realistic images. However, since path tracing requires the calculation of a large number of light paths, its computational cost is very high, especially when dealing with scenes with complex materials and fine details.

[0003] Pre-calculation is an important step in path tracing, which usually involves pre-calculating the lighting information in the scene so that this information can be quickly obtained during the actual rendering process. Traditional pre-calculation methods often do not take into account the differences in the effects of different materials on light propagation, which may result in unnecessary calculation burden and reduced rendering efficiency when processing scenes with multiple material types and properties.

[0004] With the development of rendering technology and the improvement of users' requirements for rendering quality, how to improve rendering efficiency while ensuring image quality has become an important challenge facing the industry.

[0005] Therefore, the prior art has defects and needs to be improved. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a method for optimizing path tracing pre-calculation based on material parameter technology to achieve a more efficient and intelligent rendering process.

[0007] The technical solution of the present invention is as follows: a method for optimizing path tracing pre-calculation based on material parameter technology is provided, comprising the following steps:

[0008] S1: Scene upload stage; the user logs in to the management system of the offline rendering platform through security authentication; the user uploads or specifies the scene file to be rendered, which contains the scene's geometric data, material information, and light source configuration;

[0009] S2: Scene analysis stage; the management system of the offline rendering platform automatically parses the scene file and extracts the material properties of each object; and uses a clustering algorithm to group the materials and cluster materials with similar properties together. The material properties include: color, transparency, roughness, metallicity, refractive index, and reflectivity. The clustering algorithm adopts: any one of K-means clustering, mean shift clustering, density-based clustering method, maximum expectation (EM) clustering using Gaussian mixture model (GMM), agglomerative hierarchical clustering, and graph group detection.

[0010] S3: Pre-calculation strategy customization stage; for each type of material, the management system of the offline rendering platform determines the most suitable pre-calculation method based on its optical characteristics; and formulates the depth and sampling rate of ray tracing, as well as other related parameters of the interaction between light and materials used in the path tracing process. The most suitable pre-calculation method determined based on its optical characteristics is: for metal materials with high reflectivity, more specular reflection calculations are used; for transparent or translucent materials, more refraction and subsurface scattering calculations are used; where more means a proportion greater than 50%. Furthermore, the depth and sampling rate of ray tracing use adaptive sampling technology to adjust the sampling density and depth of ray tracing according to the characteristics of the material to reduce useless calculations and improve rendering quality.

[0011] S4: Pre-calculation execution phase; the management system of the offline rendering platform performs pre-calculation operations according to the pre-calculation strategy to generate lighting information, including the contribution values ​​of direct lighting and indirect lighting; the pre-calculation results will be stored in the cache for fast access and use during the rendering process.

[0012] S5: Rendering execution stage; according to the optimized pre-calculation parameters, the management system of the offline rendering platform uses the offline rendering platform to execute the final rendering process and generate an image with optimized lighting, i.e., the rendering result; the rendering process includes ray tracing, shadow calculation, global illumination synthesis, etc. In step S5, during the real-time rendering process, if the light source in the scene changes, the management system of the offline rendering platform automatically reclassifies the materials and adjusts the pre-calculation strategy according to the change; i.e., re-enters step S2.

[0013] S6: Output and feedback stage; users can view the rendering results through thumbnails and download or further post-process them through the management system of the offline rendering platform (for example, if they are not satisfied with the rendering results, they can manually change the rendering parameters and re-render).

[0014] Furthermore, the method for optimizing path tracing pre-calculation based on material parameter technology also includes, S7: resource recovery and maintenance stage: after completing the rendering task, the management system of the offline rendering platform recovers the resources allocated to the task and performs necessary maintenance work, such as cache cleaning and hardware checking, to prepare for the next rendering task.

[0015] Furthermore, the management system of the offline rendering platform evaluates the performance of the pre-computation and rendering process through performance monitoring tools, including rendering time, resource usage, and possible optimization suggestions.

[0016] The present invention can effectively improve rendering efficiency by intelligently analyzing and applying material parameters to reduce unnecessary calculations in the path tracing pre-calculation process, thereby speeding up the overall rendering time.

[0017] The present invention can effectively enhance image quality: while ensuring rendering speed, it ensures that the pre-calculation method can take into account the impact of different materials on light propagation to maintain or improve the quality of the final image.

[0018] The present invention can effectively optimize resource allocation: reasonably allocate computing resources according to the characteristics of the material, avoid excessive calculation on materials with less visual impact, and ensure that key materials are adequately processed.

[0019] The present invention can effectively improve the level of automation: reduce the user's manual adjustment and intervention in the pre-calculation stage, make the rendering process more automated, and reduce the operational difficulty and technical threshold.

[0020] The present invention can effectively adapt to complex scenes: for complex scenes containing materials of various types and attributes, an effective processing method is provided to deal with problems that are difficult to solve with traditional pre-calculation methods.

[0021] The present invention can effectively expand the scope of technical application: by optimizing the pre-calculation method, the path tracing technology can be more widely used in movies, games, architectural visualization and other industries that require high-quality rendering.

[0022] The present invention can effectively promote sustainable development: by reducing the consumption of computing resources and lowering energy usage, it helps to promote the sustainable development of the rendering industry.

[0023] In general, the present invention aims to provide an efficient, intelligent and environmentally friendly solution for offline rendering platforms by introducing optimization technology based on material parameters to meet the growing rendering needs and quality standards.

[0024] By adopting the above scheme, the present invention provides a method for optimizing path tracking pre-calculation based on material parameter technology, which has the following technical effects:

[0025] Performance improvements: The computational complexity of shadow precomputation has been reduced by reducing the number of lights that must be processed, resulting in significantly faster rendering and overall system performance.

[0026] Resource conservation: The optimized method utilizes computing resources more efficiently, reduces dependence on high-performance hardware, and reduces hardware costs and energy consumption.

[0027] Improved image quality: Despite the reduced computational effort, the final output shadow effects remain high quality and realistic thanks to accurate handling of key light sources and smart compositing techniques.

[0028] Enhanced adaptability: This method can adapt to different rendering environments and scene changes, especially for dynamically changing light sources and complex scenes, and provides a flexible processing strategy.

[0029] User experience optimization: Speeds up rendering time, provides users with faster feedback, and simplifies the operation process because automated clustering and pre-calculation reduce the need for manual adjustments by users.

[0030] Scalability: The technology can be easily integrated into existing rendering systems, whether in a small personal studio or a large-scale render farm.

[0031] Improved intelligence level: The introduction of intelligent decision support, such as automatic identification of key light sources and automatic adjustment of pre-calculation parameters, improves the intelligence level of the rendering system.

[0032] Compatibility and maintainability: Due to the use of standardized clustering algorithms and pre-computation techniques, this method is easy to maintain and upgrade, while also being compatible with a variety of file formats and rendering engines.

[0033] In general, the shadow pre-computation optimization method based on light source clustering technology has technically achieved a double improvement in rendering efficiency and image quality, while providing higher system flexibility and user-friendliness. These technical effects make this method have important application value and competitive advantages in the offline rendering industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0035] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] See also Figure 1 The present invention provides a method for optimizing path tracing pre-calculation based on material parameter technology, comprising the following steps:

[0037] S1: Scene upload stage; the user logs in to the management system of the offline rendering platform through security authentication; the user uploads or specifies the scene file to be rendered, which contains the scene's geometric data, material information, and light source configuration;

[0038] S2: Scene analysis stage; the management system of the offline rendering platform automatically parses the scene file and extracts the material properties of each object; and uses a clustering algorithm to group the materials and cluster materials with similar properties together. The material properties include: color, transparency, roughness, metallicity, refractive index, and reflectivity. The clustering algorithm adopts: any one of K-means clustering, mean shift clustering, density-based clustering method, maximum expectation (EM) clustering using Gaussian mixture model (GMM), agglomerative hierarchical clustering, and graph group detection.

[0039] S3: Pre-calculation strategy customization stage; for each type of material, the management system of the offline rendering platform determines the most suitable pre-calculation method based on its optical characteristics; and formulates the depth and sampling rate of ray tracing, as well as other related parameters of the interaction between light and materials used in the path tracing process. The most suitable pre-calculation method determined based on its optical characteristics is: for metal materials with high reflectivity, more specular reflection calculations are used; for transparent or translucent materials, more refraction and subsurface scattering calculations are used; where more means a proportion greater than 50%. Furthermore, the depth and sampling rate of ray tracing use adaptive sampling technology to adjust the sampling density and depth of ray tracing according to the characteristics of the material to reduce useless calculations and improve rendering quality.

[0040] S4: Pre-calculation execution phase; the management system of the offline rendering platform performs pre-calculation operations according to the pre-calculation strategy to generate lighting information, including the contribution values ​​of direct lighting and indirect lighting; the pre-calculation results will be stored in the cache for fast access and use during the rendering process.

[0041] S5: Rendering execution stage; according to the optimized pre-calculation parameters, the management system of the offline rendering platform uses the offline rendering platform to execute the final rendering process and generate an image with optimized lighting, i.e., the rendering result; the rendering process includes ray tracing, shadow calculation, global illumination synthesis, etc. In step S5, during the real-time rendering process, if the light source in the scene changes, the management system of the offline rendering platform automatically reclassifies the materials and adjusts the pre-calculation strategy according to the change; i.e., re-enters step S2.

[0042] S6: Output and feedback stage; users can view the rendering results through thumbnails and download or further post-process them through the management system of the offline rendering platform (for example, if they are not satisfied with the rendering results, they can manually change the rendering parameters and re-render).

[0043] In this embodiment, the method for optimizing path tracing pre-calculation based on material parameter technology also includes, S7: resource recovery and maintenance stage: after completing the rendering task, the management system of the offline rendering platform recovers the resources allocated to the task and performs necessary maintenance work, such as cache cleaning and hardware checking, to prepare for the next rendering task.

[0044] In this embodiment, the management system of the offline rendering platform evaluates the performance of the pre-computation and rendering process, including rendering time, resource usage, and possible optimization suggestions, through a performance monitoring tool.

[0045] Specifically, the present invention performs the following operations.

[0046] Material parameter analysis: First, analyze the material properties of the objects in the scene and extract the parameters of each material, including but not limited to diffuse reflection, specular reflection, transparency, refractive index, etc.

[0047] Material clustering: Use clustering algorithms to classify materials into different categories based on material parameters, so as to facilitate subsequent targeted processing. K-means clustering algorithm is preferred.

[0048] Pre-calculation strategy customization: formulate corresponding pre-calculation strategies according to the characteristics of different types of materials. For example, for high-gloss materials, more specular reflection calculations may be required; while for translucent or transparent materials, focus on refraction and subsurface scattering effects.

[0049] Adaptive sampling optimization: During the path tracing process, adaptive sampling technology is used to adjust the sampling density and depth of ray tracing according to the characteristics of the material to reduce useless calculations and improve rendering quality.

[0050] Precomputed result cache: effectively store and manage precomputed lighting information for quick retrieval and application during rendering, reducing repeated calculations.

[0051] Real-time dynamic adjustment: During the rendering process, the pre-calculation strategy and related parameters are dynamically adjusted according to the real-time monitored rendering performance and the quality requirements specified by the user to adapt to the changing rendering needs.

[0052] Synthesis and post-processing: Finally, the contribution values ​​pre-calculated from different materials are synthesized, which may involve post-processing steps such as color correction, denoising, blurring, etc. to ensure the visual effect of the image.

[0053] Performance evaluation and feedback: Implement a performance evaluation mechanism to evaluate the optimized pre-computation method, including rendering time, resource utilization efficiency, and image quality, and make continuous improvements based on feedback.

[0054] Through the above technical solutions, the present invention can perform targeted pre-calculation optimization for different material characteristics, significantly improve the rendering efficiency of path tracing, while maintaining or improving the quality of rendered images, and is suitable for offline rendering platforms and high-performance computing environments.

[0055] In summary, the present invention provides a method for optimizing path tracing pre-calculation based on material parameter technology, which has the following technical effects:

[0056] Performance improvements: The computational complexity of shadow precomputation has been reduced by reducing the number of lights that must be processed, resulting in significantly faster rendering and overall system performance.

[0057] Resource conservation: The optimized method utilizes computing resources more efficiently, reduces dependence on high-performance hardware, and reduces hardware costs and energy consumption.

[0058] Improved image quality: Despite the reduced computational effort, the final output shadow effects remain high quality and realistic thanks to accurate handling of key light sources and smart compositing techniques.

[0059] Enhanced adaptability: This method can adapt to different rendering environments and scene changes, especially for dynamically changing light sources and complex scenes, and provides a flexible processing strategy.

[0060] User experience optimization: Speeds up rendering time, provides users with faster feedback, and simplifies the operation process because automated clustering and pre-calculation reduce the need for manual adjustments by users.

[0061] Scalability: The technology can be easily integrated into existing rendering systems, whether in a small personal studio or a large-scale render farm.

[0062] Improved intelligence level: The introduction of intelligent decision support, such as automatic identification of key light sources and automatic adjustment of pre-calculation parameters, improves the intelligence level of the rendering system.

[0063] Compatibility and maintainability: Due to the use of standardized clustering algorithms and pre-computation techniques, this method is easy to maintain and upgrade, while also being compatible with a variety of file formats and rendering engines.

[0064] In general, the shadow pre-computation optimization method based on light source clustering technology has technically achieved a double improvement in rendering efficiency and image quality, while providing higher system flexibility and user-friendliness. These technical effects make this method have important application value and competitive advantages in the offline rendering industry.

[0065] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing path tracing pre-calculation based on material parameter technology, characterized in that: The following steps are involved: S1: The user logs in to the management system of the offline rendering platform through security authentication; the user uploads or specifies the scene file to be rendered, which contains the scene's geometric data, material information, and light source configuration; S2: The management system of the offline rendering platform automatically parses the scene file and extracts the material properties of each object. It also uses a clustering algorithm to group materials and bring together materials with similar properties. S3: For each type of material, the management system of the offline rendering platform determines the most suitable pre-calculation method based on its optical properties; and determines the depth and sampling rate of ray tracing, as well as other relevant parameters of the interaction between light and materials used in the path tracing process; S4: The management system of the offline rendering platform performs pre-computation operations according to the pre-computation strategy to generate lighting information, including the contribution values ​​of direct lighting and indirect lighting; S5: According to the optimized pre-calculated parameters, the management system of the offline rendering platform uses the offline rendering platform to perform the final rendering process and generate an image with optimized lighting, i.e., a rendering result; S6: Users can view the rendering results through thumbnails and download or further post-process them through the management system of the offline rendering platform.

2. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The method further includes: S7: after completing the rendering task, the management system of the offline rendering platform recycles the resources allocated to the task and performs necessary maintenance work to prepare for the next rendering task.

3. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: In step S5, during the real-time rendering process, if the light source in the scene changes, the management system of the offline rendering platform automatically reclassifies the materials and adjusts the pre-calculation strategy according to the change; that is, re-enters step S2.

4. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The material properties include: color, transparency, roughness, metallicity, refractive index, and reflectivity.

5. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The most suitable pre-calculation method is determined based on its optical properties: for metal materials with high reflectivity, more specular reflection calculations are used; for transparent or translucent materials, more refraction and subsurface scattering calculations are used; among them, more means that the proportion is greater than 50%.

6. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The rendering process steps include ray tracing, shadow calculation, and global illumination synthesis.

7. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The depth and sampling rate of ray tracing use adaptive sampling technology to adjust the sampling density and depth of ray tracing according to the characteristics of the material to reduce useless calculations and improve rendering quality.

8. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The precomputed results will be stored in a cache for fast access and use during rendering.

9. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The management system of the offline rendering platform uses performance monitoring tools to evaluate the performance of the pre-computation and rendering process, including rendering time, resource usage, and possible optimization suggestions.

10. The method for optimizing path tracing pre-calculation based on material parameter technology according to claim 1, characterized in that: The clustering algorithm adopts: any one of K-means clustering, mean shift clustering, density-based clustering method, maximum expectation clustering using Gaussian mixture model, agglomerative hierarchical clustering, and graph group detection.

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