Contextual Media Filter Search Using Object Recognition
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Solution Overview
Problem
Existing augmented reality systems lack the ability to dynamically generate and display contextual media content that interacts with real-world environments in a user-friendly and efficient manner.
Innovation Solution
A contextual media filter system that captures an image frame, identifies objects, retrieves relevant media content from a repository, and displays it within the frame based on object recognition and geometric verification, using a client device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If augmented reality systems use traditional static media display methods, then system complexity is reduced, but user engagement and interactivity are insufficient
Solution Approach 1:
The patent implements dynamic media filters that automatically update and change based on real-time environmental conditions detected by sensors. The media content transitions from static to dynamic, adapting to user movement, lighting changes, and contextual factors, thereby enhancing interactivity without requiring complex manual control systems
Solution Approach 2:
The system employs automated media generation and selection algorithms that independently process sensor data and generate appropriate media responses without user intervention. The computational system self-adjusts media parameters based on environmental feedback, reducing the need for complex user interface controls while maintaining high interactivity
2Adaptability or versatility
If augmented reality systems implement dynamic media generation, then user experience is enhanced, but processing time and computational resources increase
Solution Approach 1:
The system pre-processes and caches media assets and computational models before they are needed. By preparing media templates, geometric verification algorithms, and sensor data processing pipelines in advance, the system minimizes real-time processing delays when dynamic media generation is triggered during AR operation
Solution Approach 2:
The patent replaces traditional mechanical or manual media selection processes with automated computational systems using machine learning algorithms and geometric verification. This substitution enables rapid, automated media generation and matching based on environmental sensors, significantly reducing processing time compared to manual or rule-based systems
3Measurement precision
If object recognition and geometric verification are implemented, then media content accuracy is improved, but system complexity and computational load increase
Solution Approach 1:
The patent divides the complex object recognition and verification process into separate modular components: initial object detection, geometric feature extraction, template matching, and verification. This segmentation allows each component to be optimized independently and processed in sequence, managing computational complexity while maintaining high accuracy through specialized processing stages
Data Source
AI summary
Method for receiving an input onto a graphical user interface at a client device, capturing an image frame at the client device, the image frame comprising a depiction of an object, identifying the object within the image frame, accessing media content associated with the object within a media repository in response to identifying the object, and causing presentation of the media content within the image frame at the client device.