3D Scene Intent Inference Using a Personal Knowledge Base
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Solution Overview
Problem
Existing computer systems struggle to provide personalized and efficient assistance to users in three-dimensional environments by accurately interpreting user intent and generating relevant actions based on user-specific knowledge, leading to inefficiencies and increased power consumption.
Innovation Solution
A computer system that utilizes image sensors to detect data representing a scene, determines user intent, and selects a personalized knowledge base to generate actions that satisfy specific criteria, reducing the need for user inputs and optimizing power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the computer system uses a personalized knowledge base to generate relevant actions, then user interaction accuracy is improved, but system complexity increases
Solution Approach 1:
The knowledge base is segmented into personalized user profiles containing preferences, habits, and context-specific information. This segmentation allows the system to retrieve only relevant portions of the knowledge base for each user interaction, improving accuracy while managing complexity through modular organization of user-specific data structures.
Solution Approach 2:
An intermediary processing layer is introduced between image sensor input and action generation. This layer infers user intent by mediating between raw scene data and the personalized knowledge base, using intermediate representations to bridge the gap between visual input and contextual understanding, thereby improving accuracy without directly increasing overall system complexity.
2Measurement precision
If the system processes complete scene data to determine user intent, then interaction accuracy is improved, but power consumption increases
Solution Approach 1:
The system extracts only the essential and relevant features from complete scene data rather than processing all available information. By taking out and focusing on critical elements such as key objects, user actions, and contextual cues, the system maintains interpretation accuracy while significantly reducing the computational power required for processing.
Solution Approach 2:
The system applies partial processing by selectively analyzing portions of the scene data that are most relevant to determining user intent. Rather than exhaustively processing the entire scene, the system performs sufficient analysis on critical regions and objects, achieving adequate accuracy with reduced energy expenditure.
3Productivity
If the system generates automated actions based on user intent, then user interaction efficiency is improved, but the number of user inputs required decreases which reduces control precision
Solution Approach 1:
The system incorporates feedback mechanisms where generated actions are presented to the user for confirmation or correction. This feedback loop allows the automated system to learn from user responses and adjust future actions, maintaining high efficiency while preserving user control precision through iterative refinement and validation of generated actions.
Solution Approach 2:
The system performs preliminary analysis and generates candidate actions before final execution. By preparing multiple potential actions and presenting them to the user in advance, the system improves efficiency through pre-processing while maintaining control precision by allowing user selection or modification of the preliminary generated actions.
Data Source
AI summary
An example process includes: detecting, via at least the one or more image sensors, first data that represents a first scene; and in response to detecting, via at least the one or more image sensors, the first data that represents the first scene and after an inference about a user intent with respect to the first scene is determined based on the first data that represents the first scene: in accordance with a determination that a portion of a knowledge base is selected based on the inference about the user intent with respect to the first scene, wherein the knowledge base is personal to a user of the computer system, and in accordance with a determination that a first action satisfies a set of action criteria, performing the first action, wherein the first action is generated based on the selected portion of the knowledge base.