Pass-Through CGR Recommendations for Personalized Low-Power Delivery
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Solution Overview
Problem
Existing systems in computer-generated reality environments fail to provide seamless integration of user-specific content, leading to overwhelming information delivery that does not align with user interests, and inefficient power usage.
Innovation Solution
A system that integrates user-specific computer-generated reality (CGR) content by recognizing and responding to the user's location, and providing personalized content items, such as a cupcake recipe or nutritional information for a cupcake are generated and displayed to the user when a cupcake is recognized within the user's field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system provides comprehensive information about recognized objects, then the user receives complete data, but the user experiences overwhelming information delivery
Solution Approach 1:
The system applies local quality by delivering personalized content tailored to each user's specific interests and context. Instead of providing uniform comprehensive information about all recognized objects, the system filters and prioritizes information based on individual user profiles, ensuring that only relevant information is delivered to each user.
Solution Approach 2:
The system changes the parameter of information delivery by dynamically adjusting content based on user context, location, and preferences. The system modifies information parameters (such as level of detail, type of information, and presentation format) according to real-time user state and environmental conditions.
2Speed
If the system continuously processes and displays content, then the user receives real-time information, but the device consumes excessive power
Solution Approach 1:
The system implements periodic action by monitoring user context and environmental conditions at intervals rather than continuously processing all data. The system activates intensive processing only when triggered by specific events (such as object recognition or location changes) and maintains lower-power operation during stable states.
Solution Approach 2:
The system applies self-service by using user-generated data and contextual information to automatically determine when and what content to deliver. The system leverages user profiles and historical data to predict information needs, reducing the need for continuous active processing and enabling more efficient power management.
3Adaptability or versatility
If the system integrates user-specific content dynamically, then the recommendation becomes personalized, but the system complexity increases
Solution Approach 1:
The system applies preliminary action by pre-processing and storing user profiles, preferences, and contextual data in advance. The system prepares recommendation algorithms and content filters beforehand, allowing for rapid personalized content generation when triggered by specific events without requiring complex real-time computation.
Solution Approach 2:
The system uses an intermediary approach by introducing a content recommendation module that acts as a mediator between the object recognition system and the content delivery system. This intermediary layer processes and filters information based on user context, simplifying the overall system architecture while enabling personalized content integration.
Data Source
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AI summary
An electronic device: obtains pass-through image data characterizing a field of view captured by an image sensor; determines whether a recognized subject in the pass-through image data satisfies a confidence score threshold associated with a user-specific recommendation profile; generates one or more computer-generated reality (CGR) content items associated with the recognized subject in response to determining that the recognized subject in the pass-through image data satisfies the confidence score threshold; and composites the pass-through image data with the one or more CGR content items, where the one or more CGR content items are proximate to the recognized subject in the field of view.