Multi-User Device Customization From Group Image Appearance
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Solution Overview
Problem
Existing electronic devices lack the ability to automatically customize user interfaces based on the appearances of multiple users in a captured image, limiting personalized and efficient customization across devices.
Innovation Solution
An electronic device captures an image of multiple users, detects and analyzes their appearances using AI functionality, and automatically generates customizations such as color or pattern changes for each user's device, communicating these customizations to associated devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual customization is used for each user, then personalization can be achieved, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables self-service customization by automatically analyzing group images and generating personalized device customizations for multiple users without requiring manual intervention. The electronic device autonomously detects users, extracts appearance features, and applies customizations based on detected characteristics.
Solution Approach 2:
The system performs preliminary customization actions by pre-processing group images and pre-generating customization parameters before users need them. When a group image is captured, the system immediately begins analyzing appearances and preparing customizations, so that when users view the image, their devices are already customized or ready for customization.
2Productivity
If automatic customization based on group images is implemented, then efficiency and personalization are improved, but the device complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that includes a customization manager and image analysis module. These intermediaries handle the complex tasks of image processing, user detection, appearance analysis, and customization generation, shielding users from the underlying complexity while enabling efficient automatic customization.
Solution Approach 2:
The customization process is segmented into distinct functional modules: image capture, user detection, appearance analysis, customization parameter generation, and device application. Each module handles a specific aspect of the process, making the overall complex system manageable through functional decomposition.
3Reliability
If customizations are generated for multiple users from a single image, then synchronization across devices is enhanced, but the measurement and detection difficulty increases
Solution Approach 1:
The system employs universal image analysis techniques that can handle multiple users and various appearance characteristics through a single multi-functional detection process. The same image processing pipeline that detects one user can simultaneously detect and analyze multiple users, extracting diverse appearance features (colors, patterns, styles) from a single group image.
Data Source
AI summary
An electronic device captures an image of a group of multiple users. Two or more users of the group of multiple users that are included in the image are detected. For each of the two or more users, a customization for the user is automatically generated based at least in part on the appearance of the user in the image (e.g., apparel worn by the first user in the image). Additionally, for each of the two or more users, the electronic device associated with the user is automatically customized based at least in part on the customization generated for the user. The customization can be, for example, a color or pattern to be displayed on an electronic device associated with the first user.