Description:TECHNICAL FIELD

[0001] This disclosure relates to a method for progressive 3D texture streaming in web-based environments such as virtual tours, online gaming, and digital showrooms, wherein textures are dynamically loaded, prioritized, and streamed based on a user’s field of view (FOV) to optimize memory management and rendering performance. More particularly, the disclosure pertains to a technique that leverages selective, on-demand texture loading to efficiently utilize GPU and browser memory, preventing slowdowns, crashes, and excessive data usage while enhancing user experience, improving workflow efficiency for digital artists, and ensuring compatibility across various hardware configurations and web browsers.

BACKGROUND OF INVENTION

[0002] In recent years, the demand for high-quality 3D content has increased across industries such as gaming, virtual real estate, digital showrooms, and online interactive experiences. Web-based 3D applications, in particular, have grown in popularity due to their accessibility, allowing users to engage with immersive environments directly through a browser without requiring dedicated software or powerful hardware. However, delivering high-resolution 3D models with detailed textures remains a significant challenge due to browser limitations, hardware constraints, and network bandwidth restrictions.

[0003] Traditional 3D rendering approaches require either preloading all textures, which leads to excessive memory usage and performance issues, or heavily compressing textures, resulting in degraded visual quality. Many existing solutions rely on static texture streaming techniques that do not dynamically adjust to a user’s field of view (FOV) or the real-time rendering needs of a web-based environment. Furthermore, optimizing textures manually for different platforms is a time-consuming process for digital artists and developers, adding complexity to the content creation workflow.

[0004] Existing virtual texturing (VT) methods have primarily been designed for desktop applications and high-performance gaming systems, where dedicated GPUs and memory management techniques can handle large texture datasets efficiently. However, when applied to web-based platforms, these methods often fail to deliver seamless performance due to browser memory limitations and the absence of direct low-level GPU access. Additionally, many conventional VT techniques require extensive manual configuration, limiting their scalability for large-scale applications.

[0005] Therefore, there is a need for an improved method of progressive 3D texture streaming that dynamically prioritizes, loads, and removes textures based on real-time user interaction. Such a method should optimize GPU and browser memory usage, enhance rendering efficiency, and provide a scalable solution that minimizes the need for manual texture optimization while maintaining high visual fidelity across different hardware and browser configurations.

[0006] While some virtual texturing (VT) techniques offer partial solutions, they are typically optimized for desktop applications and game engines rather than web environments with browser-imposed limitations. Various approaches for texture streaming and memory optimization exist in the prior art. For example, the following patents are referenced for their relevant teachings and are incorporated herein by reference.

[0007] U.S. patent publication no.US10810784B1 discloses a system and method for improved texture mapping and graphics processing, wherein whole or partial texture blocks are prefetched into an intermediate cache by a processing unit, allowing subsequent retrieval by the same or another processing unit. In this process, prefetch requests are throttled to prevent excessive memory and interconnect system load, and deduplication of prefetch requests is performed at the intermediate cache or processing unit. Additionally, an efficient technique for calculating the address of the next texture block to be prefetched is implemented. However, in the present invention, texture streaming is dynamically prioritized based on a user’s field of view (FOV) in a web-based environment, ensuring optimal memory management and rendering performance. Moreover, the present invention reduces unnecessary texture loads in real-time, improving efficiency for browser-constrained applications.

[0008] Chinese Patent No. CN112017271A discloses graphics systems and methods for using sparse textures, wherein a graphics processor memory management system supports textures that are not fully bound in memory throughout their lifetime. In this process, sparse textures are divided into fixed-size pages, and during execution, certain pages can be mapped to physical memory and populated with underlying data as needed. Additionally, statistics from the graphics processor may be utilized to determine whether a given texture or portion thereof requires physical memory allocation. The system also includes mechanisms to enforce ordering guarantees when memory availability is limited. However, in the present invention, texture streaming is adaptively managed based on real-time user interaction in web-based environments, dynamically prioritizing texture loading based on the field of view (FOV).

[0009] U.S. patent publication no. US8681169B2 discloses systems and methods for texture processing, wherein a sparse texture residency translation map is created to facilitate texture lookup operations. The method includes performing a probe process utilizing the sparse texture residency translation map information to return the finest level of detail (LOD) containing the texels for a texture lookup operation. The finest LOD is then used as a minimum LOD clamp during the lookup process, ensuring efficient texture retrieval. The translation map assigns a finest LOD number per tile of a sparse texture, indicating the minimum resident LOD, which helps in texture management. However, unlike the prior art, which focuses on LOD-based sparse texture residency, the present invention dynamically prioritizes texture streaming based on the user’s field of view (FOV) in real time. This ensures efficient memory utilization and seamless rendering in web-based environments without reliance on precomputed LOD clamping.

[0010] U.S. patent publication no. US20200380734A1 discloses graphics processor memory management systems that enable the use of sparse textures, which are not fully backed in memory throughout their lifetimes. The disclosed method divides sparse textures into fixed-dimension pages, allowing a user to selectively map certain pages to physical memory during execution. Additionally, statistical data from the graphics processor may be used to determine whether a texture or portion of a texture requires physical memory backing. The system also enforces ordering guarantees to manage cases where available memory is insufficient to back all requested pages. However, the present invention dynamically streams and prioritizes textures based on real-time user interaction and field of view (FOV).

[0011] U.S. patent publication no. [XXXXXXX] discloses a technique for texture filtering that transitions between mipmaps of different texture resolutions. The method introduces an offset (or bias) to delay the transition from a lower-resolution mipmap to a higher-resolution mipmap until the higher-resolution mipmap has been fully loaded. Additionally, a nonlinear filter is used to determine interpolation weightings, with an initial slope higher than that of standard trilinear filtering, ensuring a smoother transition between mipmap levels. However, disclosed method adaptively loads and replaces texture data based on field of view (FOV) and user navigation patterns, ensuring efficient memory usage and optimized rendering performance without requiring preloaded mipmaps.

[0012] There are disadvantages associated with the prior art. One of the disadvantages is that many existing systems rely on prefetching entire texture blocks into an intermediate cache, which can lead to excessive memory usage and inefficient resource allocation, especially in web-based environments with limited GPU and browser memory.

[0013] Another disadvantage associated with the prior art is that sparse texture mapping techniques often require manual intervention or predefined mapping strategies, which may not dynamically adjust to real-time user interactions. This results in inefficient memory allocation, as textures that are not immediately required may still consume system resources.

[0014] Still another disadvantage associated with the prior art is that mipmap-based texture filtering methods introduce delays and biases to ensure smoother transitions, but they do not actively optimize texture streaming based on user movement, leading to unnecessary memory usage and slower texture loading in interactive 3D environments.

[0015] Another disadvantage associated with the prior art is that existing methods for managing texture residency rely heavily on statistical predictions or fixed logic for determining which texture pages should remain in memory. These approaches may fail to adapt efficiently to varying network conditions, leading to either unnecessary delays in texture loading or excessive bandwidth consumption.

[0016] Yet another disadvantage associated with the prior art is that they do not effectively balance texture quality with memory constraints in real-time applications. Many implementations either sacrifice visual fidelity by over-compressing textures or cause performance issues by attempting to load high-resolution textures without efficient prioritization.

[0017] Still another disadvantage associated with the prior art is that many traditional texture streaming methods do not account for browser-based rendering constraints, requiring additional optimizations that are not inherently supported by web technologies. This results in poor scalability for complex 3D environments across different devices and platforms.

[0018] A further disadvantage associated with the prior art is that digital artists and developers must manually optimize textures or work within strict texture budgets to ensure compatibility with existing streaming methods. This adds complexity to the development workflow and limits creative flexibility.

[0019] Another disadvantage associated with the prior art is that existing solutions often fail to dynamically remove unnecessary textures from memory once they are no longer in view, leading to inefficient memory management and potential performance degradation over time.

[0020] Yet another disadvantage associated with the prior art is that they are not designed to handle varying network speeds effectively. Many implementations either assume a stable high-bandwidth connection or fail to adapt streaming quality based on real-time bandwidth fluctuations, causing either lag or degraded texture quality.

[0021] Still another disadvantage associated with the prior art is that they do not seamlessly integrate with all web browsers and hardware configurations. While some solutions perform well on certain platforms, others require additional modifications or optimizations, making cross-platform compatibility a challenge.

[0022] A further disadvantage associated with the prior art is that they do not provide an efficient mechanism to reduce latency when streaming high-resolution textures, particularly in highly interactive 3D environments such as virtual tours, gaming, and online showrooms.

[0023] Another disadvantage associated with the prior art is that most prior art techniques focus on optimizing texture streaming at the system level without considering the end-user experience, leading to potential visual inconsistencies such as delayed texture loading, blurriness, or pop-in effects.

[0024] Yet another disadvantage associated with the prior art is that many prior art systems require additional hardware support or proprietary solutions, making them less accessible for a broader range of devices, including older mobile phones and lower-end laptops.

PROBLEM TO BE SOLVED

[0025] It is, therefore, desirable to provide a system and method that addresses the above-mentioned challenges. Specifically, it is desirable to provide a method for progressive 3D texture streaming in web-based environments that dynamically loads, prioritizes, and streams textures based on a user’s field of view (FOV) while efficiently managing memory and rendering performance. Further, there is a need for a method that reduces manual texture optimization efforts, ensures seamless high-quality rendering without overloading GPU memory, and adapts to varying network conditions and hardware limitations. Additionally, the method should be scalable, compatible across different web browsers and devices, and provide an optimal balance between performance and visual fidelity for interactive 3D applications.

OBJECT OF THE INVENTION

[0026] Therefore, the object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that overcomes the disadvantages associated with the prior art.

[0027] Another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that dynamically loads, prioritizes, and streams 3D textures based on a user’s field of view (FOV), ensuring efficient memory management and rendering performance.

[0028] Yet another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that minimizes GPU memory consumption by adaptively loading only visible textures, preventing memory overuse, crashes, and excessive load times.

[0029] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that enhances real-time rendering performance by leveraging intelligent prefetching and cache optimization techniques, reducing latency in texture loading.

[0030] Still another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that enables seamless texture loading, eliminating texture pop-in effects and ensuring a smooth, uninterrupted user experience.

[0031] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that is hardware-agnostic and compatible with various system configurations and web browsers, ensuring broader accessibility and usability.

[0032] Another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that reduces the need for manual texture optimization, improving workflow efficiency for digital artists, game developers, and 3D content creators.

[0033] Yet another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that optimizes network bandwidth usage by adaptively adjusting texture streaming based on real-time network conditions, reducing unnecessary data transfers.

[0034] Still, another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that ensures high-quality rendering without overloading GPU and browser memory, enhancing performance for web-based virtual reality (VR), augmented reality (AR), and gaming applications.

[0035] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that supports scalable and modular integration into various web-based applications, such as virtual tours, architectural visualizations, online gaming, and digital showrooms.

[0036] Yet another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that dynamically adjusts texture resolution based on scene complexity and user interaction patterns, maintaining an optimal balance between performance and visual fidelity.

[0037] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that minimizes latency in texture loading and unloading, ensuring instantaneous response to user movement and interactions in 3D environments.

[0038] Still, another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that optimizes resource allocation, reducing rendering bottlenecks and improving frame rate stability in complex 3D scenes.

[0039] Yet another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that supports adaptive texture resolution scaling, dynamically lowering or increasing texture quality based on available GPU, CPU, and memory resources.

[0040] Still another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that reduces development and maintenance complexity by automating texture streaming and memory management processes for web-based 3D applications.

[0041] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that reduces power consumption, making it suitable for low-power mobile and embedded devices.

[0042] Yet another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that reduces initial loading times, allowing instantaneous access to web-based 3D applications without lengthy pre-loading phases.

[0043] A further object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that ensures low-latency texture retrieval, enabling fast rendering speeds for real-time applications like simulations, training modules, and virtual collaboration.

[0044] Still, another object of the present invention is to provide a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization that enables cost-effective deployment by reducing server-side storage and data transmission costs, making it ideal for cloud-based rendering platforms.

SUMMARY OF THE INVENTION

[0045] The present invention provides a method for progressive 3D texture streaming in web-based environments with dynamic memory optimization, ensuring efficient, high-quality rendering while minimizing memory and bandwidth consumption. The invention enables real-time texture streaming where only the required texture data is progressively loaded based on user interaction and camera movement, preventing unnecessary memory allocation and reducing data transmission costs.

[0046] The present method for progressive 3D texture streaming in web-based environments with dynamic memory optimization comprises the steps of:
I. Loading an initial 3D model with minimal texture resolution to ensure fast scene initialization;
II. Detecting user interaction, camera movement, and field of view (FOV) to determine the required texture regions;
III. Progressively loading higher-resolution textures only for visible surfaces, while keeping background textures at lower resolutions;
IV. Dynamically unloading textures that are no longer needed, optimizing GPU memory usage;
V. Implementing adaptive streaming logic to adjust texture quality based on available bandwidth, hardware capabilities, and network conditions;
VI. Supporting multi-resolution texture formats and efficient compression techniques to reduce data transmission costs;
VII. Ensuring seamless texture transitions by utilizing advanced mipmapping and LOD (Level of Detail) techniques;
VIII. Enabling compatibility with existing web standards and rendering pipelines, facilitating easy integration into modern web applications.

[0047] The present method ensures that web-based 3D environments can deliver high-quality textures without excessive loading times while significantly reducing system resource consumption. By progressively streaming only the necessary textures at any given moment, the invention eliminates performance bottlenecks, texture pop-ins, and memory overload issues common in traditional rendering approaches. Furthermore, the method provides a cost-effective and scalable solution for large-scale applications such as online simulations, virtual real estate, and industrial visualization, without requiring extensive server-side resources.

Justification:
[0048] The proposed method addresses major limitations of existing 3D texture streaming techniques, including:
I. Excessive memory consumption, where full-resolution textures are loaded unnecessarily, leading to crashes or degraded performance;
II. High bandwidth usage, as traditional methods transmit large amounts of texture data upfront instead of progressively;
III. Texture pop-ins and visual artifacts, caused by inefficient loading mechanisms that lead to noticeable delays in texture appearance;
IV. Inefficient resource management, where redundant or off-screen textures remain loaded, consuming GPU and CPU resources;
V. Lack of scalability, as prior methods struggle with large-scale 3D environments, making them impractical for web-based applications;
VI. Incompatibility with limited-resource devices, restricting access to high-quality 3D visualization on mobile and older hardware;
VII. Poor browser performance, where traditional methods are not optimized for web-based rendering pipelines, causing slowdowns.

[0049] Therefore, the present method provides a novel and efficient approach to 3D texture streaming in web-based environments, enhancing rendering performance, optimizing memory usage, and enabling high-fidelity real-time visualization across a wide range of devices and platforms. It offers an adaptive, scalable, and cost-effective solution for web-based 3D applications while ensuring smooth user experiences, reduced infrastructure costs, and improved accessibility across multiple devices and network conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

[0050] A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization, according to a preferred embodiment of the present invention, as herein described and illustrated in the accompanying drawings, are as follows:
FIG. 1 – illustrates a system flow diagram demonstrating the method for progressive 3D texture streaming in web-based environments with dynamic memory optimization. The figure comprise of:
I. pre-processing stage, including texture atlas generation, mipmap creation, compression, UV mapping, and data storage;
II. page determination process, showing how only the visible parts of textures are selected based on camera view and real-time scene analysis;
III. texture streaming workflow, including the GPU-based rendering pass for identifying required texture pages, asynchronous data fetching, decompression, and GPU memory upload;
IV. page cache management, representing texture tracking, eviction policies (Least Recently Used strategy), and cache updates to optimize memory utilization dynamically.

DETAILED DESCRIPTION OF THE INVENTION

[0051] A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization of the present invention is described with numerous specific details so as to provide a complete understanding of the invention. However, these specific details are exemplary details and should not be treated as a limitation to the scope of the invention. Throughout this specification, the word “comprise” or variations such as “comprises or comprising”, will be understood to imply the inclusions of a stated element, integer or step, or group of elements, integers, or steps, but not the exclusions of any other element, integer or step or group of elements, integers or steps.

[0052] Referring to the drawing, particularly Fig. 1, a system flow diagram demonstrating the method for progressive 3D texture streaming in web-based environments with dynamic memory optimization is shown. The present invention relates to an optimized system and method for Sparse Virtual Texturing (SVT), designed to enhance real-time rendering performance by dynamically streaming texture data based on visibility, screen-space importance, and rendering context. Traditional rendering approaches often require storing large, high-resolution textures entirely in memory, leading to excessive VRAM consumption and performance bottlenecks. Further, the disclosed system mitigates these issues by implementing an intelligent, on-demand texture streaming technique that selectively loads only the most relevant texture data required for rendering at any given moment. This reduces memory overhead while preserving visual fidelity, making it particularly advantageous for applications such as real-time graphics rendering in video games, virtual reality (VR), augmented reality (AR), digital simulations, and high-fidelity visualizations. However, the potential of the present invention extends far beyond gaming, offering immense value in industries such as film rendering, geographic information systems (GIS), medical imaging, automotive design, cloud computing, artificial intelligence, military simulations, industrial training, and virtual retail experiences.

[0053] The present method begins with a preprocessing stage, where raw high-resolution textures undergo tiling and segmentation to facilitate efficient storage and retrieval. Instead of handling entire textures as monolithic images, the system decomposes them into smaller, fixed-size texture pages, typically in dimensions that may be 128×128, 256×256, or 512×512 pixels, forming a virtual texture atlas. This atlas functions as a unified storage structure where all texture pages are indexed and stored according to a predefined mipmap hierarchy. The hierarchical organization ensures that multiple levels of detail (LODs) are available, allowing the rendering system to dynamically adjust texture resolution based on an object’s distance from the camera. Additionally, the virtual texture atlas is designed for efficient GPU memory management, ensuring that texture pages are readily available for rendering while maintaining minimal memory footprint. The segmentation process is followed by texture format optimization, where each texture page is stored in a GPU-friendly, compressed format that may be BC1–BC7 (Block Compression), ASTC (Adaptive Scalable Texture Compression), or ETC (Ericsson Texture Compression). These compression techniques reduce VRAM usage without significantly degrading texture quality, allowing high-resolution textures to be streamed efficiently while minimizing bandwidth consumption.

[0054] Once textures have been preprocessed and stored in the virtual texture atlas, the system transitions into the real-time rendering phase, where texture streaming decisions are made dynamically based on visibility analysis. The Page ID Buffer plays a central role in this process. Unlike traditional rendering pipelines that store direct texture references in material shaders, the Page ID Buffer stores lightweight texture page indices instead. During rendering, each visible fragment is assigned a corresponding Page ID, which maps to a specific texture page in the virtual texture atlas. The system evaluates texture page visibility through a structured sequence of steps:
I. Before streaming any texture pages, the system performs camera frustum culling, ensuring that only objects within the camera’s viewing frustum are considered for rendering. Any object outside the field of view is ignored, preventing unnecessary texture streaming;
II. To further optimize texture selection, the system executes a depth prepass, identifying objects that are occluded by other geometry. Texture pages for hidden objects are excluded from streaming, reducing redundant memory usage;
III. Once visible objects have been determined, the system calculates their relative screen-space importance. Larger objects occupying more screen space receive higher priority for high-resolution textures, whereas smaller, less significant objects are assigned lower-resolution texture pages.

[0055] After determining which texture pages are required for rendering, the system initiates asynchronous texture streaming, where missing pages are fetched from disk, cloud storage, or remote texture servers in parallel with the rendering process. Unlike conventional methods that cause stuttering when loading large textures, the disclosed system asynchronously loads individual texture pages in smaller, manageable chunks, ensuring uninterrupted performance. The streaming pipeline is managed by a multi-threaded texture loading mechanism, which operates independently of the primary rendering loop. This architecture allows textures to be fetched, decompressed, and stored in GPU memory without blocking frame execution. Additionally, the system employs an intelligent prefetching algorithm that predicts future texture needs based on camera motion vectors, gameplay patterns, and historical texture usage data. This approach reduces texture loading latency, ensuring that required textures are available before they are needed.

[0056] To further optimize memory efficiency, the system implements a dynamic VRAM cache allocation strategy, where texture pages are stored in a GPU-resident texture cache managed using an LRU (Least Recently Used) eviction policy. The cache automatically prioritizes frequently accessed texture pages while discarding less relevant ones, ensuring optimal memory utilization. In cases where memory constraints become critical, the system employs compressed texture residency, where infrequently accessed textures remain in a compressed format until needed, minimizing GPU memory consumption.

[0057] As the camera navigates through the virtual environment, the system dynamically adjusts texture resolution to balance performance and visual fidelity. The adaptive LOD mechanism ensures that near-field objects receive the highest-resolution textures to maintain detailed visual quality, mid-range objects utilize medium-resolution textures to optimize memory usage, and far-field objects rely on low-resolution mipmaps, conserving resources while maintaining perceptual consistency. To ensure seamless transitions between texture LODs, the system employs temporal coherence techniques, smoothing texture resolution changes over multiple frames to eliminate noticeable "texture pop-in" artifacts. The system also incorporates anisotropic filtering, dynamically adjusting texture sharpness at oblique viewing angles to enhance surface detail while maintaining performance efficiency.

[0058] To ensure that the system scales across various hardware configurations, adaptive performance heuristics are integrated, thereby allowing real-time texture streaming to adjust based on GPU memory availability, CPU-GPU bandwidth constraints, and frame rate targets. The system also supports multi-GPU configurations, enabling parallelized texture streaming for high-end rendering applications. Additionally, the present incention is designed to function across a broad range of hardware and browser environments, with compatibility extending to mobile devices released in the past 4–5 years and desktop/laptop systems from the last 8–9 years, provided they feature sufficient GPU processing capabilities and high-bandwidth, low-latency network access. While Chromium-based browsers (that may be Chrome, Edge, or Brave) fully support the necessary WebGL/WebGPU APIs for optimal SVT execution, non-Chromium browsers that may be Firefox and Safari require certain optimizations to be disabled, resulting in marginal performance trade-offs. In edge cases involving older or low-end hardware, adaptive modifications such as alternative caching mechanisms, reduced texture resolution, or adjusted streaming parameters may be necessary to ensure stable operation. Any such implementations must adhere to manufacturer firmware constraints, third-party software agreements, and applicable intellectual property rights governing GPU memory management and web-based rendering. Users are responsible for ensuring compliance with evolving browser and hardware standards, mitigating potential compatibility limitations, and aligning with best practices in security, licensing, and regulatory requirements.

[0059] The disclosed method comprises steps:
I. Loading an initial 3D model with minimal texture resolution to ensure fast scene initialization;
II. Detecting user interaction, camera movement, and field of view (FOV) to determine the required texture regions;
III. Progressively loading higher-resolution textures only for visible surfaces, while keeping background textures at lower resolutions;
IV. Dynamically unloading textures that are no longer needed, optimizing GPU memory usage;
V. Implementing adaptive streaming logic to adjust texture quality based on available bandwidth, hardware capabilities, and network conditions;
VI. Supporting multi-resolution texture formats and efficient compression techniques to reduce data transmission costs;
VII. Ensuring seamless texture transitions by utilizing advanced mipmapping and LOD (Level of Detail) techniques;
VIII. Enabling compatibility with existing web standards and rendering pipelines, facilitating easy integration into modern web applications.

[0060] In another embodiment, the texture streaming pipeline may integrate ray tracing techniques for enhanced visibility determination. Ray intersection tests are used to determine which texture pages contribute to reflections, shadows, and global illumination, ensuring that texture resources are allocated efficiently based on lighting interactions. Further, the present invention may utilize AI-driven predictive algorithms, where a trained neural network analyzes historical gameplay data, user behavior patterns, and scene context to anticipate upcoming texture requirements. This enables proactive texture streaming, reducing latency and improving rendering efficiency.

[0061] Further, in another embodiment, the present invention may adapt for cloud gaming platforms, where textures are streamed dynamically over a network instead of being stored locally. This approach utilizes delta encoding and progressive texture transmission, ensuring minimal bandwidth consumption while delivering high-quality textures in real-time. Moreover, the disclosed invention may integrate GPU-accelerated procedural texture synthesis, thereby allowing missing texture details to be dynamically generated on-the-fly instead of relying solely on pre-stored texture data. This approach is particularly effective for organic materials such as terrains, skies, and natural surfaces, reducing reliance on large texture datasets.

[0062] Furthermore, in another embodiment of the disclosed invention, GPU-accelerated procedural texture synthesis may be integrated, thereby allowing missing texture details to be dynamically generated on-the-fly instead of relying solely on pre-stored texture data. This approach is particularly effective for organic materials such as terrains, skies, and natural surfaces, reducing reliance on large texture datasets.

[0063] Certain features of the invention have been described with reference to the example embodiments. However, the description is not intended to be construed in a limiting sense. Various modifications of the example embodiments as well as other embodiments of the invention, which are apparent to the persons skilled in the art to which the invention pertains, are deemed to lie within the spirit and scope of the invention. , Claims:We claim :

1. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization, comprising the steps of:
– packing multiple textures into a virtual texture atlas using a binary-tree algorithm so as to manage texture page allocation efficiently;
– generating mipmaps for each texture page so as to enable adaptive level-of-detail rendering;
– compressing texture pages using GPU-friendly formats so as to optimize memory usage and reduce bandwidth consumption;
– mapping textures onto 3D models through parameterization (UV mapping) so as to ensure proper texture alignment;
– adding border padding to each texture page so as to prevent texture bleeding during rendering;
– storing the preprocessed texture data in a local disk, cloud storage, or content delivery network (CDN) for on-demand retrieval;
– identifying 3D objects in the scene using their respective mesh data and UV coordinates;
– rendering a Page ID Buffer in a dedicated GPU pass, wherein each pixel encodes a texture page identifier corresponding to a region in the texture atlas;
– extracting the required page identifiers from the Page ID Buffer while filtering out occluded or off-screen textures so as to minimize redundant streaming;
– managing a request queue for missing texture pages, prioritizing those closer to the camera or essential for scene rendering;
– asynchronously fetching texture pages from the storage medium while allowing rendering so as to proceed without interruption;
– decompressing retrieved texture pages using decompression techniques;
– uploading the decompressed texture pages into GPU memory and organizing them within a GPU-resident texture cache;
– prefetching predicted texture pages based on camera motion vectors, gameplay patterns, and historical texture access data;
– tracking texture usage frequency and assigning priority based on recent access history;
– evicting less important texture pages using a Least Recently Used (LRU) eviction policy when GPU memory is constrained;
– retaining infrequently accessed textures in a compressed format until needed, thereby minimizing VRAM consumption;
– assigning high-resolution textures to near-field objects, medium-resolution textures to mid-range objects, and low-resolution mipmaps so as to far-field objects;
– employing temporal coherence techniques to prevent texture pop-in artifacts when switching between mip levels; and
– utilizing anisotropic filtering to enhance texture sharpness at oblique viewing angles while optimizing GPU workload.

2. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the binary-tree algorithm used for texture packing dynamically optimizes the spatial arrangement of texture pages within the virtual texture atlas to minimize fragmentation and improve lookup efficiency.

3. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the compression formats for texture pages that may be BCn (Block Compression), ASTC (Adaptive Scalable Texture Compression), or ETC (Ericsson Texture Compression), are selected adaptively based on device capabilities, network conditions, and scene complexity.

4. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the Page ID Buffer is implemented as a frame buffer object (FBO), wherein each fragment encodes a unique page identifier for efficient texture lookup during rendering.

5. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the asynchronous texture streaming process utilizes multi-threading, web workers, or GPU compute shaders to accelerate data retrieval and decompression without stalling the rendering pipeline.

6. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the LRU eviction policy dynamically adjusts its eviction threshold based on available VRAM and current rendering load to balance performance and memory efficiency.

7. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the prefetching algorithm employs machine learning-based predictive modeling, wherein an AI-driven neural network analyzes past camera movements and interaction patterns to anticipate future texture requests.

8. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein the ray tracing techniques are integrated for enhanced visibility determination, ensuring that texture pages contributing to reflections, shadows, and global illumination are prioritized in the streaming process.

9. A method for progressive 3D texture streaming in web-based environments with dynamic memory optimization as claimed in claim 1, wherein GPU-accelerated procedural texture synthesis is utilized as a fallback mechanism to dynamically generate missing texture details instead of retrieving them from pre-stored texture datasets, reducing bandwidth dependency.