AR Typography Personalization With Real-Time Editable Overlays
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Solution Overview
Problem
Existing augmented reality systems lack the ability to allow users to edit and personalize real-world typography in real-time, limiting the interactive and dynamic enhancement of text in captured images or videos.
Innovation Solution
An augmented reality personalization system that enables users to detect, analyze, and edit typography in real-time using Natural Feature Tracking (NFT) techniques, allowing for real-time updates and edits to be shared across multiple devices through networked features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If augmented reality systems use traditional text detection methods, then text can be detected in images, but users cannot edit or personalize the typography in real-time
Solution Approach 1:
The system segments the typography editing process into distinct components: text detection, text recognition, editable text overlay generation, and original text preservation. This segmentation allows users to personalize typography while maintaining the original text's visual characteristics, resolving the contradiction between adaptability and complexity by breaking down the complex personalization task into manageable steps
Solution Approach 2:
The system adds a new dimension to AR text interaction by enabling temporal editing capabilities. Instead of static text detection, the system creates an editable text overlay that exists in a new temporal dimension, allowing real-time modifications while the original text remains preserved in its original form. This dimensional addition enables personalization without fundamentally redesigning the entire system
2Ease of operation
If the system allows real-time editing of typography, then user interaction and personalization improve, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary text detection and recognition before the user begins editing. By pre-processing the image to identify and extract text regions, the system prepares the groundwork for editing without requiring real-time processing during user interaction. This preliminary action reduces processing time during the actual editing phase while maintaining ease of operation
Solution Approach 2:
The system creates a copy of the original text as an editable overlay rather than modifying the original text directly. This copying approach allows users to interact with the text freely while the original text remains intact and can be referenced for accuracy. The copy mechanism enables easy editing without the computational overhead of real-time image manipulation
3Reliability
If the system maintains the original look and feel of text during editing, then text authenticity is preserved, but editing flexibility is limited
Solution Approach 1:
The system applies local quality by preserving the original text's visual characteristics (font, size, color, style) in the background while allowing users to make local edits to the copied text overlay. Users can modify specific portions of the text (individual words, phrases, or characters) without affecting the overall appearance and authenticity of the original text. This local differentiation enables both authenticity preservation and editing flexibility simultaneously
Data Source
AI summary
Disclosed are augmented reality (AR) personalization systems to enable a user to edit and personalize presentations of real-world typography in real-time. The AR personalization system captures an image depicting a physical location via a camera coupled to a client device. For example, the client device may include a mobile device that includes a camera configured to record and display images (e.g., photos, videos) in real-time. The AR personalization system causes display of the image at the client device, and scans the image to detect occurrences of typography within the image (e.g., signs, billboards, posters, graffiti).