Machine Learning Lighting Control for Audio Video Adaptation
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Solution Overview
Problem
Current lighting control solutions for non-professional applications lack artistic connotation and are limited by pre-deterministic approaches, failing to account for a wide range of sound and video combinations, making them unsuitable for consumer markets and amateur users.
Innovation Solution
A machine learning-based approach that simulates lighting design by generating command cues, allowing for non-pre-deterministic lighting control through supervised, unsupervised, and reinforced learning phases, integrating user feedback to adapt lighting responses to various audio and video events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pre-deterministic sound-light or video-light settings are used, then lighting control is automated and synchronized with audio/video events, but the system lacks artistic connotation and cannot handle a wide range of sound and video combinations
Solution Approach 1:
The system incorporates feedback loops where the lighting controller continuously monitors audio and video inputs, analyzes their characteristics, and dynamically adjusts lighting parameters in response. This feedback mechanism enables the system to adapt to a wide variety of sound and video combinations while maintaining artistic quality, as the controller learns from observed patterns and user preferences over time
Solution Approach 2:
The patent employs parameter changes by dynamically adjusting multiple lighting parameters (intensity, color temperature, timing, duration) based on the characteristics of audio and video inputs. The controller modifies these parameters in real-time according to the analyzed content, enabling versatile adaptation to different media while preserving artistic connotation through intelligent parameter selection
2Ease of operation
If professional lighting design processes are used, then artistic connotation and quality lighting control are achieved, but the process is time-consuming and requires specialized technical knowledge
Solution Approach 1:
The lighting controller operates autonomously by automatically analyzing audio and video inputs, generating appropriate lighting commands, and executing control decisions without requiring manual intervention from light designers. The system performs self-learning and self-optimization based on observed patterns and feedback, thereby achieving professional-quality lighting control while eliminating the time-consuming design and testing processes
Solution Approach 2:
The patent replaces the mechanical process of manual lighting design and testing with an automated electronic system that uses signal processing, pattern recognition, and control algorithms. This substitution eliminates the need for specialized human expertise and extensive time investment, while maintaining or improving lighting control quality through consistent, data-driven decision-making
Data Source
AI summary
A lighting control apparatus for producing control signals or cues for controlling operating parameter of one or more controlled lighting devices, including a learning machine configured for performing: a supervised learning phase, wherein, as a function of a first set of audio and/or video files coupled with a first set of control signals, the machine produces mapping rules between the audio and/or video files and the control signals of these first sets; an unsupervised learning phase wherein the machine receives a second set of audio and/or video files and produces, from the second set of audio and/or video files, a second set of control signals as a function of the mapping rules. The learning machine may be configured to carry out a reinforced learning phase with the production of an evaluation ranking of the mapping rules and the possible elimination of mapping rules.