Augmented Object Personalization Using Context Vectors in AR
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Solution Overview
Problem
Existing digital media objects, such as greeting cards, do not adapt their content based on the receiver or context, limiting their utility for communication and entertainment.
Innovation Solution
A system that uses a database mapping multimedia content to target objects, leveraging context vectors and sensor data to superimpose personalized augmented reality presentations on digital media, allowing dynamic content adaptation based on user context and interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital media objects (e.g., greeting cards) use fixed static content, then manufacturing and distribution are simple, but the objects cannot adapt to different recipients or contexts, reducing their utility and engagement value
Solution Approach 1:
The patent implements dynamic content delivery by transitioning from static digital media to augmented reality experiences that adapt in real-time. The system dynamically selects and renders multimedia content based on contextual parameters (location, time, user profile) and sensor data (device orientation, movement), allowing greeting cards and similar objects to transform from fixed images to interactive 3D experiences that respond to user actions and environmental conditions.
Solution Approach 2:
The system changes multiple parameters simultaneously to achieve hyper-personalization: it modifies content selection based on user profile parameters, adjusts rendering perspective based on device sensor parameters (accelerometer, gyroscope), and adapts the augmented reality experience based on contextual parameters (GPS location, timestamp). This multi-parameter approach enables the same base object to generate infinitely varied personalized experiences.
2Ease of operation
If digital media objects remain static and non-interactive, then the system is simple to operate, but the receiver cannot interact with or change the content, limiting entertainment and communication value
Solution Approach 1:
The system implements continuous feedback loops where sensor data from the mobile device (accelerometer, gyroscope, camera) feeds back to the augmented reality rendering engine, which adjusts the displayed content in real-time. User interactions such as device movement, rotation, or gestures trigger recalculation of the augmented reality scene, creating an interactive experience where the system responds to user actions. This feedback mechanism transforms static media into dynamic conversations between user and content.
3Reliability
If augmented reality content is highly personalized using user profiles and sensor data, then user engagement and perceived utility increase, but processing requirements and computational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing user profile data, contextual information, and multimedia content associations in databases before actual augmented reality rendering. Context vectors are pre-computed and stored, allowing the system to quickly retrieve and match appropriate content during runtime without performing complex calculations in real-time. This pre-computation significantly reduces processing requirements during the actual augmented reality experience.
Solution Approach 2:
The patent introduces context vectors as intermediary data structures that mediate between raw sensor data/user profiles and the final content selection. Instead of directly comparing complex user profiles with vast content libraries, the system transforms both into comparable context vectors (numerical representations) that can be efficiently matched. This intermediary representation simplifies the matching process and reduces computational complexity while maintaining personalization accuracy.
Data Source
AI summary
A system for presenting hyper-personalized content over objects is provided. The system determines context features based on digital media, sensor data, and a user profile of a user of a mobile device. The system computes a context vector representing a context associated with the digital media and the user based on a correlation of the context features and compares the context vector with a plurality of context vectors of a plurality of multimedia content. The system selects, from the plurality of multimedia content, a multimedia content based on the comparison of the context vector with the plurality of context vectors. The system renders, on a display of the mobile device, an augmented reality presentation in which the selected multimedia content is superimposed on a target object displayed in the digital media. The augmented reality presentation is hyper-personalized to map to the context associated with the user.