Automated Lighting Scene Creation from Image Color Palettes
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Solution Overview
Problem
Users find it time-consuming and cumbersome to create lighting scenes based on images, as existing systems require high user involvement and may not accurately capture the desired color palette due to image imperfections or the need to select specific images.
Innovation Solution
A method that automatically creates lighting scenes by selecting and merging images based on common parameters, using clustering algorithms to group images by features like color and saturation, and detecting trigger events such as increased image activity or social media interactions to suggest scenes with minimal user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually select and configure images to create lighting scenes, then the color palette can be customized to match user preferences, but the process becomes time-consuming and requires high user involvement
Solution Approach 1:
The system automatically performs image selection, color extraction, and scene configuration without requiring user intervention. The processor autonomously identifies trigger events, selects relevant images, extracts color palettes, and configures lighting devices based on extracted colors, enabling the system to serve itself in the scene creation process.
Solution Approach 2:
The system pre-processes images by extracting color palettes and storing them in association with trigger events before user requests. When a trigger event occurs, the pre-extracted color information is immediately available for rapid scene configuration, eliminating the need for real-time image processing and reducing scene creation time.
2Manufacturing precision
If users manually select specific images for scene creation, then the color palette can be precisely controlled, but the process becomes cumbersome and complex
Solution Approach 1:
The system automatically performs image selection, color extraction, and scene configuration without requiring user intervention. The processor autonomously identifies trigger events, selects relevant images, extracts color palettes, and configures lighting devices based on extracted colors, enabling the system to serve itself in the scene creation process.
Solution Approach 2:
The system monitors trigger events such as message receipts, image uploads, or social media interactions and uses this feedback to automatically initiate the scene creation process. The feedback mechanism allows the system to respond to user actions without requiring explicit commands, simplifying the interaction while maintaining color accuracy.
3Productivity
If the system automatically creates lighting scenes without user input, then the process becomes quick and simple, but the color palette may not accurately match user preferences
Solution Approach 1:
The system monitors trigger events such as message receipts, image uploads, or social media interactions and uses this feedback to automatically initiate the scene creation process. The feedback mechanism allows the system to respond to user actions without requiring explicit commands, simplifying the interaction while maintaining color accuracy.
Solution Approach 2:
The system automatically performs image selection, color extraction, and scene configuration without requiring user intervention. The processor autonomously identifies trigger events, selects relevant images, extracts color palettes, and configures lighting devices based on extracted colors, enabling the system to serve itself in the scene creation process.
4Adaptability or versatility
If multiple images are merged to create a scene, then the color palette becomes more comprehensive, but the process requires more processing steps and user involvement
Solution Approach 1:
The system pre-processes images by extracting color palettes and storing them in association with trigger events before user requests. When a trigger event occurs, the pre-extracted color information is immediately available for rapid scene configuration, eliminating the need for real-time image processing and reducing scene creation time.
Solution Approach 2:
The system automatically performs image selection, color extraction, and scene configuration without requiring user intervention. The processor autonomously identifies trigger events, selects relevant images, extracts color palettes, and configures lighting devices based on extracted colors, enabling the system to serve itself in the scene creation process.
Data Source
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AI summary
A method for automatically creating lighting settings based on an image or images. An event associated with such images can be detected, such as the uploading of a number of photos to a gallery, or the posting of an image on social media. By assessing the event, and the image or images, it is possible to determine whether and how to create a new lighting scene. If multiple images are present, it may be possible to group or merge the images to downselect to one or a small number of images, or image parameters. The lighting scene or scenes can then be created based on these images or parameters. For example, a scene can be created to mimic the colour palette, or even to attempt to mimic or reflect shapes or distributions of light or colour in the image.