Video Feed Mapping for Camera-Aligned Eye Contact in Calls
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital communication platforms fail to dynamically adjust interface elements for optimal eye contact during communication sessions, particularly when participants' cameras are positioned differently from the default assumptions, leading to a lack of perceived engagement and fatigue.
Innovation Solution
A system that allows participants to designate camera locations relative to their display, determines highlighted video feeds, and assigns new locations within the user interface to align with these designated camera positions, ensuring optimal eye contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system uses default camera location assumptions, then the interface configuration is simple, but the perceived eye contact and participant engagement deteriorate
Solution Approach 1:
The system automatically detects camera locations using computer vision technology to identify where participants are looking, and self-adjusts the positioning of video feeds without requiring manual user configuration. This eliminates the need for users to manually configure camera locations while maintaining accurate eye contact representation.
Solution Approach 2:
The system dynamically changes the positional parameters of video feeds based on detected eye gaze directions. By continuously adjusting video feed positions according to detected eye contact patterns, the system adapts the interface configuration to match actual participant engagement without manual intervention.
2Reliability
If the system manually configures camera locations, then the eye contact accuracy improves, but the device complexity increases
Solution Approach 1:
The system replaces manual mechanical configuration operations with automated computer vision-based eye tracking technology. Instead of requiring users to manually position camera icons and configure settings, the system uses optical detection of eye gaze directions to automatically determine and apply appropriate video feed positioning.
Solution Approach 2:
The system introduces an intermediary eye tracking module that detects gaze directions and translates them into positioning instructions for video feeds. This intermediary layer automates the complex configuration process by serving as a mediator between participant behavior and interface arrangement.
3Reliability
If the system dynamically adjusts video feed positions, then participant engagement improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs eye contact detection and video feed repositioning at periodic intervals rather than continuously, reducing computational overhead while maintaining effective engagement. By updating positions at strategically chosen moments during the communication session, the system balances engagement quality with processing efficiency.
Data Source
AI summary
Techniques for automatic mapping of highlighted video feeds to detected camera locations are disclosed. In an example method, a client device detects one or more locations of one or more cameras communicatively coupled to the client device joined to a communication session. The client device includes one or more displays and provides a user interface (UI) for the communication session. The UI includes one or more video feeds associated with participants of the communication session. The client device identifies one or more highlighted video feeds within the communication session. The client device automatically assigns a new location within the UI for each of the one or more highlighted video feeds corresponding to the one or more locations relative to the one or more displays of the client device.