Dynamic Group Selection for Prominent Participant Camera Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Videoconferencing systems face challenges in maintaining prominent participants within the camera's field of view as they move, and in establishing and maintaining a desired location and size of participants within the frame.
Innovation Solution
A system and method that extracts visual information from the camera's field of view, determines prominent participants, generates a group selection prioritizing them, parameterizes this selection to adjust dynamically, and tracks their position using camera adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the camera field of view is fixed, then the system structure is simple, but prominent participants cannot be maintained within the frame when they move
Solution Approach 1:
The system transitions from a fixed camera field of view to a dynamic tracking system that automatically adjusts the field of view to follow prominent participants. The camera parameters (position, orientation, zoom) are dynamically modified based on real-time detection of prominent participants, ensuring they remain within the frame while accommodating movement.
Solution Approach 2:
The system implements a feedback loop where the camera continuously detects prominent participants, determines their positions, and adjusts the field of view accordingly. This closed-loop control ensures that prominent participants are maintained within the frame by constantly monitoring their positions and making real-time camera adjustments.
2Adaptability or versatility
If the camera continuously tracks and adjusts to follow participants, then participants remain in frame, but the system complexity and computational requirements increase
Solution Approach 1:
The system pre-defines a set of camera parameters (pan, tilt, zoom, focus) that can be adjusted to track participants. By establishing this parameterization framework in advance, the system can quickly adapt to participant movements without complex real-time calculations, as the adjustment space is already structured and constrained.
3Measurement precision
If the system extracts and processes visual information to identify prominent participants, then accurate tracking is achieved, but processing time and computational resources increase
Solution Approach 1:
The system processes visual information to detect prominent participants rather than analyzing all objects in the scene. By focusing computational resources on identifying and tracking only the prominent participants (a subset of all objects), the system achieves accurate tracking while reducing overall processing time and computational burden.
Data Source
AI summary
A computer system may execute a computer-implemented method that includes extracting visual identifiers from within a field of view of a camera. The method includes determining, based on the extracted visual identifiers, one or more prominent participants within the field of view. The method further includes generating, based on the extracted visual identifiers and the one or more prominent participants, a group selection that prioritizes the one or more prominent participants. The method further includes parameterizing the group selection such that the group selection dynamically adjusts to include the prominent participants within the field of view of the camera. The method further includes tracking, via a camera, the parameterized group selection.