Media Item Selection Using Similarity Vectors for Faster Sharing
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Solution Overview
Problem
Sharing media items from mobile devices is time-consuming due to the need for manual selection and review of multiple items, especially videos, which prolongs the upload process.
Innovation Solution
A mobile device processes media items by generating feature vectors to identify metrics, automatically selecting similar items based on characteristics like geographic location, time, and facial features, and displaying them in three-dimensional or two-dimensional representations for efficient selection and transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection of media items is used, then user control over selection is improved, but time required for selection increases
Solution Approach 1:
The system performs preliminary actions by automatically selecting media items based on similarity metrics before the user completes the transfer operation. When a user initiates a transfer, the system pre-selects additional media items with similar characteristics (geographic location, time, facial features) so that the user only needs to confirm rather than manually select each item, thereby reducing selection time while maintaining control.
Solution Approach 2:
The system enables self-service by autonomously identifying and selecting media items that match user preferences without requiring manual intervention. The automatic selection mechanism analyzes media characteristics and autonomously groups similar items, allowing the system to serve itself in the selection process while the user retains oversight and final approval authority.
2Loss of time
If automatic selection based on similarity metrics is used, then selection time is reduced, but selection precision may deteriorate
Solution Approach 1:
The system changes parameters by utilizing multiple similarity metrics (geographic location, time, facial features) to comprehensively evaluate media item similarity. By adjusting and weighting different parameters, the system achieves both efficient automatic selection and high precision in identifying relevant media items, resolving the trade-off between speed and accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where user selections and corrections are analyzed to refine future automatic selections. When users confirm or modify automatically selected items, this feedback is used to improve the accuracy of similarity metrics and selection algorithms, ensuring that automatic selection becomes increasingly precise over time.
3Quantity of substance
If multiple media items are selected for transfer, then sharing completeness is improved, but processing complexity increases
Solution Approach 1:
The system merges multiple media items into a single transfer operation by automatically grouping similar items together. Instead of processing each media item separately, the system combines selected items based on similarity metrics, reducing processing complexity while maintaining the ability to transfer multiple items simultaneously, thus achieving sharing completeness without proportional increase in complexity.
Data Source
AI summary
A device includes an image capture device configured to capture a first video. The device includes a memory configured to store one or more videos. The device further includes a processor coupled to the memory. The processor is configured to concatenate the first video and a second video to generate a combined video. The second video is included in the one or more videos or is accessible via a network. The second video is selected by the processor based on a similarity of a first set of characteristics with a second set of characteristics. The first set of characteristics corresponds to the first video. The second set of characteristics corresponds to the second video.