Virtual Scene Pre-loading via Predictive Interaction Tracking
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Solution Overview
Problem
Cloud-based interactive applications, such as video games, often experience noticeable delays when transitioning between scenes due to graphic-intensive content, leading to a less desirable user experience.
Innovation Solution
The system pre-loads content for subsequent virtual scenes based on predicted user interactions, allowing for immediate rendering and access without waiting, using a head-mounted display connected to a server that tracks user interactivity to anticipate and prepare the next scene.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the system loads graphic-intensive content for the next scene before the user selects it, then the wait time for scene transitions is reduced, but the system may waste resources pre-loading content that the user never selects
Solution Approach 1:
The system performs preliminary actions by pre-loading content for the next scene before the user actually selects it. The server monitors user interactions and predictive metrics in real-time, and once confidence thresholds are met, it begins loading the next scene's graphic-intensive content in advance, thereby reducing wait time during scene transitions.
Solution Approach 2:
The pre-loading process is dynamic rather than static. The system continuously monitors user interactions and adjusts the pre-loading behavior based on real-time predictive metrics. If the user changes their selection before the confidence threshold is met, the system adapts by canceling the pre-load and initiating a new prediction cycle, thus avoiding wasted resources.
2Ease of operation
If the system pre-loads content based on predicted user interactions, then user experience is improved with faster access, but the complexity of tracking and predicting user behavior increases
Solution Approach 1:
The system implements feedback loops by continuously monitoring user interactions and using this data to refine predictions. The server tracks various metrics such as gaze direction, head movements, and interaction patterns, then feeds this information back into the prediction algorithm to improve accuracy over time and make more informed pre-loading decisions.
Solution Approach 2:
The system performs self-service by automatically analyzing user behavior patterns and making intelligent predictions without requiring explicit user input. The predictive algorithm autonomously determines when to pre-load content based on observed interaction patterns, reducing the need for complex manual configuration or user setup.
3Loss of energy
If the system waits for user selection before loading the next scene, then resource usage is optimized, but the user experiences noticeable delays and frustration
Solution Approach 1:
The system takes preliminary action by initiating content loading before the user formally selects the next scene. By monitoring predictive metrics and user interactions in real-time, the system can start loading graphic-intensive content in advance, thereby improving scene access speed while managing resource usage through intelligent prediction.
Solution Approach 2:
The system skips the traditional sequential process of waiting for user selection followed by content loading. Instead, it rushes through the preparation phase by pre-loading content in parallel with ongoing user interaction analysis, effectively overlapping the loading process with the prediction process to reduce overall wait time.
Data Source
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AI summary
Methods and systems for providing access to virtual scenes of an interactive application include receiving a selection of the interactive application. In response to the selection, a virtual scene of the application is provided. Interactivity of the user detected in the virtual scene is processed to identify predicted interaction with visual options in the virtual scene. The processing continues till a threshold of actions indicative of imminent selection of one of the visual options is reached. A second virtual scene associated with the visual option that was identified to be imminently selected, is pre-loaded, based on achieving the threshold. The second virtual scene is executed using the pre-loaded content, when the visual option associated with the second virtual scene is selected, so as to enable full rendering of the second virtual scene for user interaction.