User Intention Recognition via AR Display Feedback
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Solution Overview
Problem
Existing user interface technologies, such as those relying on line-of-sight detection, often result in inaccurate grasping of user intentions due to vague or low-interest actions, leading to erroneous control.
Innovation Solution
An information processing apparatus and method that includes an accuracy acquisition unit to estimate user intentions based on action recognition results and a response-induction control unit to perform targeted effects, using augmented reality displays to confirm user interest without explicit inquiry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If line-of-sight detection is used for user interface interaction, then input interface diversity is improved, but user intention recognition accuracy deteriorates due to vague line-of-sight actions
Solution Approach 1:
The system presents candidate targets to the user and receives feedback through line-of-sight detection. The user's gaze behavior serves as feedback to confirm or reject candidate targets, enabling iterative refinement of intention recognition accuracy while maintaining interface versatility.
Solution Approach 2:
The system introduces an intermediary processing layer that interprets vague line-of-sight actions by generating multiple candidate targets and using gaze duration and patterns as mediators to determine the user's true intention, thereby resolving the ambiguity between diverse input methods and accurate intention recognition.
2Extent of automation
If action recognition is used to estimate user intention, then automation extent is improved, but intention estimation accuracy deteriorates due to low connection between vague actions and user interest
Solution Approach 1:
The system uses feedback from multiple sources including gaze duration, candidate target selection, and user responses to refine automated intention estimation. This feedback loop enables the system to distinguish between genuine user interest and incidental gaze behavior, improving accuracy while maintaining automation.
Solution Approach 2:
The system changes parameters of action recognition by considering multiple factors beyond simple gaze detection, including gaze duration, movement patterns, and contextual information. This multi-parameter approach transforms vague single-dimensional actions into rich multi-dimensional data for more accurate automated intention estimation.
3Measurement precision
If response-induction control is performed based on accuracy information, then user intention grasping accuracy is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-processing action recognition data, generating candidate targets, and preparing accuracy information before final intention determination. This preliminary processing organizes complex data into structured formats, reducing the complexity of subsequent control decisions while improving intention grasping accuracy.
Solution Approach 2:
The system segments the control process into distinct modules: action recognition, accuracy information generation, candidate target presentation, and final intention determination. This segmentation allows each module to handle specific aspects of complexity independently, making the overall system more manageable while achieving high accuracy in user intention grasping.
Data Source
AI summary
To provide an information processing apparatus, an information processing method, and a program capable of grasping a user intention more accurately. An information processing apparatus includes: an accuracy acquisition unit configured to acquire accuracy information regarding a user intention to a target, the accuracy information being estimated on the basis of an action-recognition result of a user; and a response-induction control unit configured to perform response-induction control of imparting an effect according to the acquired accuracy information, to the target.