Affinity-Based Videoconference Display Switching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current videoconferencing systems fail to provide a real-time meeting experience by randomly displaying participants from different companies or affinity groups, lacking control over which participants are shown on screens, which can be distracting and unproductive in collaborative settings.
Innovation Solution
A system and method for affinity-based switching in videoconferences that recognizes user characteristics and common interests among participants, grouping them into affinity groups based on shared traits, and intelligently switches displays to show participants with matching affinities, using URI tables, face recognition, and predefined associations to enhance user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If participants are displayed randomly on screens, then all participants can be shown, but the meeting experience becomes distracting and unproductive
Solution Approach 1:
The patent applies local quality by assigning different display priorities to different participants based on their affinity groups. Instead of random or uniform display, the system selectively prioritizes displaying participants from the same affinity group when a member is active, creating localized quality enhancement in the display strategy that improves meeting effectiveness while maintaining display flexibility.
2Productivity
If affinity-based switching is implemented, then participant grouping and focused display is achieved, but system complexity increases due to URI tables and recognition protocols
Solution Approach 1:
The patent applies preliminary action by pre-establishing affinity groups and storing them in URI tables before the videoconference begins. Participant characteristics and group associations are predetermined and organized in advance, allowing the system to quickly retrieve and apply affinity information during the conference without complex real-time analysis, thus reducing operational complexity while maintaining collaboration efficiency.
3Measurement precision
If real-time affinity recognition is performed during videoconference, then accurate participant grouping is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs affinity recognition and grouping in advance, storing participant characteristics and group associations in URI tables before the videoconference starts. This eliminates the need for complex real-time analysis during the conference, maintaining high recognition accuracy while minimizing processing delays and time loss during actual meetings.
Solution Approach 2:
The patent uses copying by storing pre-determined affinity group information in URI tables. Instead of performing complex real-time analysis, the system retrieves and uses copied affinity data that was previously established, significantly reducing computational requirements and processing time while maintaining recognition accuracy.
Data Source
AI summary
An example method may include displaying first image data associated with a first participant on a first screen; comparing a first affinity associated with the first participant to a second affinity associated with a second participant; and displaying second image data associated with the second participant on a second screen if the second affinity matches the first affinity. In certain implementations, the first data is displayed as a result of the first participant being an active speaker in a videoconference. The method may also include determining the first affinity and the second affinity based on corresponding uniform resource indicators (URIs) associated with the first affinity and the second affinity.