Visual Recognition Device Pairing via Distance Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The process of pairing wireless peripheral devices with host electronic devices is often cumbersome and non-standard, requiring manual button presses and reference to user manuals, lacking a streamlined method for accurate device recognition and connection.
Innovation Solution
Implementing a system that uses visual recognition and machine learning to pair peripheral devices with host devices by capturing images of the peripherals, determining visual and signal distances, and employing deep learning to identify the intended device based on usage patterns and historical pairing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual button pressing and user manual reference are used for device pairing, then device connection can be established, but the pairing process becomes cumbersome and time-consuming
Solution Approach 1:
The patent replaces manual mechanical button pressing with automated visual recognition technology. The host device captures images of the peripheral device using a camera sensor, and machine learning algorithms automatically identify and match the peripheral device, eliminating the need for manual button sequences and user manual reference.
Solution Approach 2:
The system enables self-service pairing where the host device autonomously identifies and pairs with the peripheral device without requiring user intervention. The machine learning model automatically processes visual data, determines device identity, and completes the pairing process independently.
2Extent of automation
If visual recognition is used to identify peripheral devices, then automatic device identification is achieved, but system complexity increases due to integration of camera sensors and machine learning models
Solution Approach 1:
The host device integrates multiple functions into a single system: the camera sensor serves both for visual recognition of peripheral devices and for determining visual distance through image analysis. The machine learning model handles both device identification and distance estimation, reducing the need for separate dedicated components.
Solution Approach 2:
The patent combines visual recognition and distance estimation functions into a unified image processing pipeline. The same camera-capture-and-analyze mechanism serves dual purposes: identifying the peripheral device type and measuring the visual distance simultaneously, rather than requiring separate sensing systems.
3Measurement precision
If visual distance and signal distance are both measured and correlated, then accurate device pairing is ensured, but measurement and processing complexity increases
Solution Approach 1:
The system implements feedback by comparing visual distance (from image analysis) with signal distance (from wireless signal strength). This cross-validation mechanism ensures accurate device pairing by verifying that both measurement methods agree on the peripheral device's identity and location, reducing false pairings.
Solution Approach 2:
The patent uses visual distance estimation as an additional verification layer beyond standard signal-based pairing. By incorporating image analysis to estimate distance and comparing it with signal strength-derived distance, the system achieves higher accuracy through slightly excessive measurement action.
Data Source
AI summary
The present disclosure is directed at pairing a host electronic device with a peripheral electronic device using visual recognition and deep learning techniques. In particular, the host device may receive an indication of a peripheral device via a camera or as a result of searching for the peripheral device (e.g., due startup of a related application or periodic scanning). The host device may also receive an image of the peripheral device (e.g., captured via the camera), and determine a visual distance to the peripheral device based on the image. The host device may also determine a signal strength of the peripheral device, and determine a signal distance to the peripheral device based on the signal strength. The host device may pair with the peripheral device if the visual distance and the signal distance are approximately equal.