AI-Driven Screen-Sharing Interface for Automatic Cross-Device Focus
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Solution Overview
Problem
Web conferencing applications often provide suboptimal user experiences when sharing content across devices with different form factors, leading to user inefficiencies and fatigue due to the need for manual zooming and adjustments to view important parts of the shared screen.
Innovation Solution
An adaptive user interface amelioration program that utilizes natural language processing, optical character recognition, and image object detection to analyze shared content and device characteristics, dynamically modifying the display to focus on relevant elements based on user profiles and device capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual zooming and adjustments are required to view important parts of the shared screen, then users can control their own viewing preferences, but user inefficiency and fatigue increase
Solution Approach 1:
The system automatically analyzes the shared screen content using NLP and object detection to identify important elements, then autonomously adjusts the viewing area and zoom level without requiring user intervention. The system serves itself by making intelligent decisions about what to highlight based on extracted textual and visual information.
Solution Approach 2:
The system performs preliminary analysis of the shared screen content before displaying it to the user. By extracting text elements, identifying objects, and determining importance in advance, the system prepares optimized viewing parameters ahead of time, eliminating the need for manual adjustment during the meeting.
2Area of stationary object
If the display shows the entire shared screen, then all content is visible, but important elements cannot be highlighted for users with smaller screens
Solution Approach 1:
The system applies different display qualities to different regions of the shared screen based on their importance. By identifying critical elements through NLP and object detection, the system enhances the local quality of those specific areas by increasing zoom level and adjusting brightness/contrast, while maintaining appropriate display for the rest of the content.
Solution Approach 2:
The display parameters are dynamically adjusted based on the detected content and device characteristics. The system continuously monitors the shared screen, identifies important elements, and real-time modifies viewing area, zoom level, and highlight parameters to adapt to different device form factors and content changes during the meeting.
3Extent of automation
If the system analyzes shared content using NLP and object detection, then relevant elements can be automatically identified, but processing time and computational resources increase
Solution Approach 1:
The system applies partial analysis by focusing computational resources on extracting only the most critical text elements and objects from the shared screen. Rather than analyzing every pixel and word, the system uses NLP to identify key concepts and object detection to locate important elements, performing just enough analysis to achieve effective content highlighting.
Data Source
AI summary
According to one embodiment, a method, computer system, and computer program product for adaptive user interface amelioration during a screen sharing session is provided. The embodiment may include receiving shared content during a screen sharing session. The embodiment may also include identifying one or more device characteristics for a user device associated with a user and one or more user profile characteristics for the user. The embodiment may further include extracting topical elements within the received shared content. The embodiment may also include identifying a location of one or more objects and/or one or more text elements in the shared content. The embodiment may further include modifying a viewing area of the shared content on a display screen of the user device.