Automated Lighting Control Using Concept Data and Reference Images
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Solution Overview
Problem
Current lighting systems require significant time and personnel to achieve desired lighting effects, as setting lighting conditions often involves trial and error, even with simulation technologies.
Innovation Solution
An information processing apparatus and method that determines and sets light emitting unit settings based on concept data indicating desired image characteristics and light emission results, allowing for automated adjustment of light sources such as intensity, color temperature, and irradiation direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If lighting conditions are set through trial and error to obtain desired lighting effect, then lighting quality is improved, but time consumption and personnel requirements increase
Solution Approach 1:
The system performs preliminary action by capturing reference images of the object under different lighting conditions before the actual photography. These reference images are used to pre-calculate optimal lighting settings, eliminating the need for trial-and-error adjustment during the actual shooting process. The control unit stores these reference images and uses them to determine lighting parameters in advance.
Solution Approach 2:
The system creates a digital copy of the lighting scenario by capturing reference images that represent different lighting conditions. Instead of physically adjusting lights and retaking images multiple times, the system uses these digital copies (reference images) to calculate and determine the optimal lighting settings, replacing physical trial-and-error with computational analysis.
2Illumination intensity
If multiple light sources are used to create stereoscopic effect, then image quality is improved, but complexity of adjustment and personnel requirements increase
Solution Approach 1:
The system implements feedback by using captured reference images to evaluate lighting effects and automatically determine optimal settings for multiple light sources. The control unit analyzes the reference images showing different lighting conditions and automatically calculates the best combination of light source settings, replacing manual adjustment complexity with automated feedback-driven optimization.
Solution Approach 2:
The system performs self-service by automatically determining lighting settings without requiring manual intervention. The control unit independently analyzes reference images and calculates optimal lighting parameters for multiple light sources, eliminating the need for skilled personnel to manually adjust each light source to achieve the desired stereoscopic effect.
3Manufacturing precision
If manual adjustment of light sources is performed, then lighting precision is improved, but operation time and skill requirements increase
Solution Approach 1:
The system replaces the mechanical system of manual light source adjustment with an automated computational system. Instead of physically adjusting light sources based on operator skill, the control unit uses image processing and calculation to automatically determine precise lighting settings, substituting human operation with automated mechanical and computational processes.
Solution Approach 2:
The system achieves precise lighting settings by automatically calculating and changing multiple lighting parameters simultaneously. The control unit determines optimal values for light source intensity, position, and other parameters based on reference image analysis, replacing manual parameter adjustment with automated parameter optimization that achieves higher precision without requiring operator skill.
Data Source
AI summary
An information processing apparatus includes a control unit configured to determine a setting of a light emitting unit according to concept data indicating a characteristic of a desired image and a light emission result of the light emitting unit.