Facial Feature Matching for Automatic Image Transfer to Known Devices
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Solution Overview
Problem
Existing electronic devices require multiple manual operations to share images with external devices, which can be cumbersome and inefficient.
Innovation Solution
An electronic device is equipped with a processor that automatically identifies facial features, matches them with stored feature points, and transmits images to compatible external devices without the need for user intervention or server services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual operations are used to share images (selecting applications, choosing images, uploading), then the user has control over the sharing process, but the operation time and complexity increase significantly
Solution Approach 1:
The electronic device automatically performs image sharing by detecting faces in captured images, identifying corresponding external devices, and transmitting images without requiring user selection or intervention. The system serves itself by autonomously completing the entire sharing workflow from detection to transmission.
Solution Approach 2:
The electronic device pre-stores feature points of multiple persons in its memory before image capture. When an image is captured, the system immediately compares detected face feature points against the pre-stored database, enabling instant identification and sharing without delays for manual processing.
2Reliability
If server services are used for image sharing, then centralized management is achieved, but device complexity and dependency increase
Solution Approach 1:
The patent extracts the core image sharing functionality from centralized server services and implements it locally within the electronic device itself. The device independently performs face recognition, feature point matching, and image transmission without relying on external server infrastructure, thereby reducing system complexity and external dependencies.
3Measurement precision
If feature point matching is performed against stored data, then accurate device identification is achieved, but data processing complexity increases
Solution Approach 1:
The system segments the face recognition process into distinct components: extracting feature points from detected faces, comparing these points against pre-stored feature point databases, and identifying matching external devices. This segmentation allows for precise matching while managing processing complexity through modular operation.
Data Source
AI summary
An example electronic device includes a communication circuit; a memory; and at least one processor. The at least one processor may be configured to store a plurality of feature points corresponding to a plurality of persons in the memory; acquire a first image; acquire a first portion in which the face of at least one person is recognized in the first image; acquire a first feature point related to the face from the first portion; identify whether a second feature point corresponding to the first feature point is present in the plurality of feature points stored in the memory; and, based on no feature point corresponding to the first feature point being identified, transmit the first feature point and information related to the first feature point to an external electronic device; based on the feature point corresponding to the feature point related to the face being stored in the external electronic device, receive identification information of the external electronic device from the external electronic device, store the received identification information; and transmit the first image to the external electronic device.