Focus Image Analysis with Probabilistic Intention Scoring
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Solution Overview
Problem
Traditional computing architectures struggle to accurately determine user focus using natural user input modalities like eye gaze, hand gestures, and voice due to sensor noise and uncertainty, leading to inaccuracies in ray-casting and hit-testing techniques.
Innovation Solution
A computer-implemented method that generates an intention image with pixels encoded based on user input, determining intention values and scores for interactive objects, leveraging the rendering system to handle probabilistic spatial distributions of user input, utilizing GPUs for parallel processing and customizable rulesets to disambiguate focus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ray-casting and hit-testing techniques are used to determine user focus, then the system can process user input, but the determination accuracy deteriorates due to sensor noise and uncertainty in natural user input modalities
Solution Approach 1:
The patent segments the user input signal processing into multiple independent evaluation dimensions (eye gaze, hand gesture, voice, body orientation) rather than treating it as a single unified signal. Each modality is processed separately to determine its individual contribution to user focus, allowing the system to handle uncertainty in each modality independently while combining their probabilistic contributions to achieve more robust focus determination
Solution Approach 2:
The patent transforms the deterministic parameters of traditional ray-casting into probabilistic parameters by introducing intention values and intention scores. Instead of treating user input as precise coordinates, the system represents them as probability distributions with associated confidence levels, allowing the rendering system to account for sensor noise and uncertainty while determining user focus
2Productivity
If the rendering system processes complex objects with traditional methods, then rendering accuracy is maintained, but rendering speed deteriorates
Solution Approach 1:
The patent replaces the traditional mechanical ray-casting algorithm with a rendering system approach that uses probabilistic intention values. Instead of computationally intensive ray tracing for each pixel, the system uses the rendering pipeline to evaluate intention scores across multiple objects in parallel, significantly improving processing speed while maintaining accuracy through the probabilistic framework
Solution Approach 2:
The patent adds a new dimension of probabilistic intention scoring to the traditional rendering pipeline. By incorporating intention values as an additional evaluation layer that works alongside traditional rendering attributes, the system can process complex objects faster while maintaining determination accuracy through the multi-dimensional evaluation approach
Data Source
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Figure 3A~3B
AI summary
A computer-implemented method for determining focus of a user is provided. User input is received. An intention image of a scene including a plurality of interactive objects is generated. The intention image includes pixels encoded with intention values determined based on the user input. An intention value indicates a likelihood that the user intends to focus on the pixel. An intention score is determined for each interactive object based on the intention values of pixels that correspond to the interactive object. An interactive object of the plurality of interactive objects is determined to be a focused object that has the user's focus based on the intention scores of the plurality of interactive objects.