Head Framing Templates for Equal Participant Attention
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Solution Overview
Problem
Existing video systems often focus on the whole room view in conference settings, leading to unequal attention on participants based on their distance from the camera, creating an inequitable meeting experience.
Innovation Solution
A video system employs a head detection model to identify individual heads, determine their number and layout, and apply templates to create customized head frames for each participant, ensuring equal representation and focus through head framing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the video system uses whole room view, then the camera can capture all participants in the room, but participants farther from the camera receive less attention and appear smaller
Solution Approach 1:
The patent divides the video stream into multiple separate video streams, with each stream corresponding to a specific participant. This segmentation allows each participant to be captured in their own dedicated frame, ensuring equal attention and consistent appearance size regardless of their distance from the camera in the original room view.
Solution Approach 2:
The patent applies different framing qualities to different participants based on their individual needs. Each participant receives a customized video stream with optimized framing that highlights their face and upper body, creating local quality enhancement for each participant while maintaining overall system functionality.
2Measurement precision
If the video system focuses on individual heads, then equal attention can be given to all participants, but the system complexity increases due to head detection and template selection
Solution Approach 1:
The patent pre-defines multiple video stream templates with different layouts and configurations. These templates are prepared in advance and stored in a library, allowing the system to quickly select and apply the appropriate template without performing complex real-time calculations. This preliminary preparation significantly reduces operational complexity while maintaining high attention equality.
Solution Approach 2:
The system changes parameters such as video stream layout, frame rate, and resolution based on the number and positions of detected heads. By selecting from pre-defined templates with different parameter sets, the system achieves adaptive behavior without the computational burden of generating custom parameters from scratch.
3Measurement precision
If the video system creates customized head frames for each participant, then meeting equity is enhanced, but processing time and computational resources increase
Solution Approach 1:
The patent pre-computes and stores multiple video stream templates with different configurations in advance. When processing occurs, the system simply selects from these pre-prepared templates rather than generating custom frames from scratch, dramatically reducing processing time while maintaining high meeting equity through customized framing for each participant.
Solution Approach 2:
The system creates customized head frames by copying and adapting from pre-defined template patterns. Instead of generating entirely new frames for each participant, the system reuses verified template structures and applies them to different participants, reducing computational resources and processing time while maintaining quality and equity.
Data Source
AI summary
A method may include obtaining, using a head detection model and for an image of a video stream, head detection information, where the head detection information identifies heads detected in the image, selecting a set of templates for the heads, and creating, individually, head frame definitions for the heads using the set of templates. The method may processing the video stream using the head frame definitions.