Video Conference Lighting Control via Illumination Model
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Solution Overview
Problem
Current video conferencing systems face challenges in optimizing lighting conditions during video conference calls, leading to suboptimal video image quality due to inadequate lighting control, which affects the overall conference experience.
Innovation Solution
A system and method that uses a video camera to capture images of a conference room, determine the lighting contribution of each light source, and generate an illumination model to adjust lighting levels dynamically during a video conference call, utilizing interactive television networks and various communication protocols to control lights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If lighting conditions are not optimized during video conference calls, then the system operation is simple, but the video image quality deteriorates
Solution Approach 1:
The system performs preliminary actions by capturing images of the conference room before the video conference call begins, and by pre-calculating and storing illumination models for different lighting scenarios. This allows the optimal lighting conditions to be established before the call starts, improving video image quality without adding complexity during the actual call.
Solution Approach 2:
The system uses feedback from captured images of the conference room to determine the actual lighting conditions and generate appropriate illumination models. The controller continuously monitors the lighting environment and adjusts the illumination accordingly, creating a closed-loop system that optimizes video image quality based on real-time feedback.
2Manufacturing precision
If dynamic lighting adjustment is implemented during video conference calls, then the lighting effect is optimized, but the system response time increases
Solution Approach 1:
The system pre-calculates illumination models for various lighting scenarios before the video conference call begins. When the call starts, the system can immediately apply the pre-computed illumination model without needing to perform complex real-time calculations, thus optimizing lighting effect while minimizing response time.
Solution Approach 2:
The system dynamically adjusts lighting based on the video conference call status. The controller monitors whether a video conference call is active and automatically applies the appropriate illumination model, enabling dynamic lighting optimization without requiring continuous real-time computation during the call.
3Manufacturing precision
If multiple lights are controlled individually, then the illumination precision is improved, but the device complexity increases
Solution Approach 1:
The system segments the lighting control into individual light or light group control units. Each light can be independently controlled based on its specific illumination characteristics and contribution to the overall lighting effect. This segmentation enables precise illumination control while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The system controls multiple lights by adjusting individual parameters such as intensity, color temperature, and on/off state for each light or light group. The controller modifies these parameters based on the generated illumination models, achieving precise illumination control without requiring complex hardware modifications.
Data Source
AI summary
A system that incorporates teachings of the present disclosure may include, for example, an apparatus having a controller to capture one or more images of a conference room using a video camera, generate an illumination model for a plurality of lights associated with the conference room based on the images, and illuminate at least a portion of the lights based on the illumination model during a video conference call that utilizes the video camera, where the video conference call is implemented using an interactive television network. Other embodiments are disclosed.