Image Grouping via Display Position Feedback
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Solution Overview
Problem
Existing image organization methods on computing devices, such as those using geographic location or facial recognition, often inaccurately group images based on user interest, leading to cluttered displays and increased user frustration as users search for specific images.
Innovation Solution
A method where a computing device assigns a perceived interest to images based on changes in display position when the image is visible, using facial recognition input to determine if another person is viewing the image, allowing images to be grouped and transferred to viewing locations that reflect user preferences, thereby reducing clutter and improving image accessibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If images are organized using geographic location or facial recognition, then images can be automatically grouped, but the grouping accuracy based on user interest deteriorates
Solution Approach 1:
The system uses display position data as feedback to continuously refine image grouping. By monitoring which images remain visible when the display is moved, the system infers user interest and adjusts grouping accordingly, creating a closed-loop system that improves accuracy over time
Solution Approach 2:
The system automatically organizes images based on inferred user interest without requiring manual user input. It self-adjusts by analyzing display position changes and image visibility patterns, enabling automated grouping that adapts to user preferences
2Ease of operation
If images are manually searched through to find specific images, then users can locate desired images, but user frustration increases and time is wasted
Solution Approach 1:
The system pre-organizes images into interest-based groups before users need to search. By proactively grouping images according to inferred user interest, the system eliminates the need for manual searching and enables users to directly access relevant image collections
Solution Approach 2:
The system divides the image collection into multiple interest-based groups or albums. This segmentation allows users to navigate to specific interest categories rather than searching through all images, significantly reducing search time and improving accessibility
3Measurement precision
If display position changes are monitored to determine user interest, then image organization accuracy improves, but device complexity increases
Solution Approach 1:
The system uses display position data as an intermediary indicator of user interest rather than directly tracking detailed user behavior. This intermediary approach simplifies the tracking system while maintaining accurate inference of user preferences through observable display movement patterns
Data Source
AI summary
Methods, apparatuses, and non-transitory machine-readable media for image location based on a perceived interest and display position. Apparatuses can include a display, a memory device, and a controller. an example controller can assign a perceived interest and sort images based in part on the perceived interest. In another example, a method can include assigning, by a controller coupled to a memory device, a perceived interest to an image of a plurality of images, wherein the perceived interest is assigned based in part on a change in position of a display coupled to the memory device while the image is viewable on the display, selecting the image from an initial viewing location on the display responsive to the assigned perceived interest, and transferring the image to a different viewing location, wherein the initial viewing location and the different viewing location are visible on the display.