Context-Based Media Curation for Image-Guided AR Presentations
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Solution Overview
Problem
Existing augmented reality systems lack the ability to curate media content based on user context, such as location and temporal data, leading to a suboptimal user experience in presenting media overlays and filters.
Innovation Solution
A context-based media curation system that identifies user context through image analysis and metadata, curates a collection of media content from a repository, and presents it in a navigable format, including augmented reality content, based on object categories and user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If augmented reality systems present media overlays and filters without context-based curation, then the system complexity is reduced, but the user experience quality deteriorates
Solution Approach 1:
The system performs preliminary analysis of user context (location, time, image content) before presenting media overlays and filters. This advance preparation allows the system to curate relevant content based on contextual understanding, improving user experience without adding complex real-time processing requirements during actual AR interaction
Solution Approach 2:
The patent introduces a context-based curation intermediary layer between the user and media content repository. This intermediary analyzes contextual data and selectively retrieves relevant media content, shielding users from the underlying system complexity while delivering personalized, context-aware media presentations
2Loss of information
If the system curates media content based on multiple context parameters, then the relevance of media content improves, but the processing time increases
Solution Approach 1:
The context analysis process is segmented into independent modules: location analysis, temporal analysis, and image content analysis. Each module processes specific aspects of context separately and contributes to the overall curation decision, allowing parallel processing and reducing total analysis time while maintaining comprehensive relevance assessment
Solution Approach 2:
The system dynamically adjusts the weight and importance of different context parameters based on the specific situation. Not all context parameters are equally relevant in every scenario, so the system adapts parameter significance to optimize processing efficiency while maintaining content relevance
Data Source
AI summary
A media curation system configured to perform operations that include, capturing an image at a client device, wherein the image includes a depiction of an object, identifying an object category of the object based on the depiction of the object within the image, accessing media content associated with the object category within a media repository, generating a presentation of the media content, and causing display of the presentation of the media content within the image at the client device.