VR/AR Web Page Delivery Using Object Loading Priority
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Solution Overview
Problem
Current technologies for delivering and performing WebVR and WebAR pages face inefficiencies in rendering and loading, particularly in prioritizing and optimizing the delivery of objects within the scene, leading to slower load times and degraded user experience.
Innovation Solution
The system asynchronously analyzes VR/AR web pages to create an object loading list (OLL) based on object characteristics such as field of view, size, and distance, allowing for prioritized delivery and prefetching of objects using HTTP/2 push and Early Hints, ensuring that critical objects are loaded before others.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If objects are loaded in the order they appear in HTML, then the delivery process is simple, but the loading speed of critical objects is slow
Solution Approach 1:
The system performs preliminary analysis of the VR/AR scene to identify critical objects before actual delivery. An object loading list is generated in advance that prioritizes objects based on their importance to the initial field of view, allowing the server to pre-fetch and prioritize delivery of critical objects before the client actually requests them.
Solution Approach 2:
The delivery process is segmented into distinct phases: HTML delivery, followed by prioritized object delivery based on the pre-generated object loading list. This segmentation allows the system to handle critical objects separately from non-critical ones, ensuring that essential VR/AR elements are loaded first while maintaining manageable complexity through structured processing.
2Loss of time
If all objects are loaded simultaneously, then the complete scene is available, but the initial field of view loading time is increased
Solution Approach 1:
The system performs preliminary analysis to identify which objects are critical for the initial field of view versus those that can be loaded later. This preliminary classification enables the server to prioritize delivery of only the most essential objects first, reducing initial loading time while ensuring that complete scene rendering remains reliable as additional objects are subsequently loaded.
Solution Approach 2:
Different delivery strategies are applied to different objects based on their local importance. Critical objects that appear in the initial field of view are delivered with high priority and prefetched in advance, while non-critical objects are delivered later. This differentiated approach ensures fast initial rendering without compromising the eventual completeness of the scene.
3Speed
If the page is analyzed synchronously, then the analysis is done before delivery, but the delivery time is increased
Solution Approach 1:
The system performs the analysis action in advance, before the actual page delivery to the client. The object loading list is generated through preliminary analysis of the VR/AR scene, allowing the server to have all necessary delivery information ready before the client request arrives, thus enabling fast delivery without sacrificing analysis accuracy.
Solution Approach 2:
The analysis is performed on a copy of the page in a non-user-facing browser environment rather than on the actual live page. This allows the system to analyze the scene structure, identify critical objects, and generate the object loading list without interfering with the actual user experience or delivery timing, maintaining both speed and precision.
4Productivity
If critical objects are identified and prioritized, then the loading speed improves, but the analysis complexity increases
Solution Approach 1:
The system analyzes a copy of the page in a controlled browser environment rather than the live production page. This copying approach allows for complex analysis of scene structure, object relationships, and field of view calculations without impacting the actual user experience or requiring modifications to the production system, thereby improving loading efficiency while managing analysis complexity.
Solution Approach 2:
A browser application serves as an intermediary between the raw HTML and the delivery system. This intermediary analyzes the VR/AR scene, identifies critical objects, and generates the object loading list, acting as a mediator that handles the complexity of analysis separately from the delivery process, thus improving overall loading efficiency without burdening the production system.
Data Source
AI summary
Among other things, this document describes systems, devices, and methods for improving the delivery and performance of web pages authored to produce virtual reality (VR) or augmented reality (AR) experiences. In some embodiments, such web pages are analyzed. This analysis may be initiated at the request of a content server that receives a client request for the HTML. The analysis may involve, asynchronous to the client request, loading the the page into a non-user-facing browser environment and allowing the VR or AR scene to execute, even including executing animation routines for a predetermined period of time. Certain characteristics of the scene and of objects are thereby captured. Based on this information, an object list ordered by loading priority is prepared. Consulting this information in response to subsequent requests for the page, a content server can implement server push, early hints and/or other delivery enhancements.