AR Scene Object Analysis for Targeted Content
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Solution Overview
Problem
Conventional techniques for targeted content delivery based on web-browsing data are inaccurate due to user deception and fail to account for physical surroundings not reflected in digital footprints.
Innovation Solution
An augmented reality (AR) analysis platform that identifies objects within an AR scene to gather information about the user's physical environment, determining visual characteristics to generate targeted content recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If web-browsing data is used for targeted content delivery, then content can be personalized based on digital footprint, but accuracy deteriorates due to user deception and inability to capture physical surroundings
Solution Approach 1:
The patent transitions from two-dimensional digital footprint data to three-dimensional physical environment data by utilizing augmented reality camera feeds. This dimensional shift enables direct observation of physical surroundings, objects, and contexts that cannot be captured through traditional web-browsing data, thereby improving accuracy while capturing previously lost physical environment information.
2Measurement precision
If AR scene analysis is implemented to capture physical environment data, then accuracy of targeted content improves, but device complexity increases
Solution Approach 1:
The system utilizes the device's existing augmented reality camera feed and processing capabilities to automatically analyze physical environments. The device serves itself by leveraging its own hardware resources (camera, processor) to generate the AR data stream that is then analyzed for targeted content, eliminating the need for separate sensing devices or complex external infrastructure.
3Adaptability or versatility
If visual characteristics of multiple objects are analyzed in AR scenes, then customization of product recommendations improves, but processing time increases
Solution Approach 1:
The system extracts only the most relevant visual characteristics from AR scenes—such as dominant colors, object categories, and key visual features—rather than analyzing all possible attributes. This selective extraction approach maintains high customization capability by focusing on the most impactful visual elements while significantly reducing processing time and computational overhead.
Data Source
AI summary
This disclosure generally covers systems and methods that identify objects within an augmented reality (“AR”) scene (received from a user) to gather information concerning the user's physical environment or physical features and to recommend products. In particular, the disclosed systems and methods detect characteristics of multiple objects shown within an AR scene received from a user and, based on the detected characteristics, select products to recommend to the user. When analyzing characteristics, in some embodiments, the disclosed systems and methods determine visual characteristics associated with the real object or virtual object, such as color or location of an object. The disclosed systems and methods, in some embodiments, then select an endorsed product to recommend for use with the real object—based on the determined visual characteristics—and create a product recommendation that recommends the endorsed product.