Virtual Keyboard Finger Detection for Fewer Typing Errors
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Solution Overview
Problem
Existing virtual keyboards on electronic devices suffer from high typographical error rates due to uniform detection of hand movements without considering the device's posture and finger position and bending, making it difficult to distinguish inputs to keys in the same column and adjust the keyboard layout.
Innovation Solution
An electronic device equipped with a camera and processor that crops images to detect finger objects, matches key columns to image regions, identifies key rows based on finger positions and bending, and determines virtual key inputs through typing movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If uniform detection of hand movements is used without considering device posture and finger position, then the detection process is simple, but the typographical error rate increases
Solution Approach 1:
The system changes detection parameters dynamically based on device posture (horizontal/vertical) and finger characteristics (position, bending degree). Instead of using fixed detection parameters, the system adjusts key column and key row determination parameters according to the detected device orientation and finger state, thereby reducing typographical errors without significantly increasing system complexity
Solution Approach 2:
The detection system transitions from a static uniform detection approach to a dynamic adaptive detection approach. The system continuously adapts detection parameters based on real-time device posture and finger position, making the detection process flexible and context-aware while maintaining reasonable complexity
2Stability of the object's composition
If key columns are fixedly matched for each user's finger without considering finger position and bending, then the keyboard layout is stable, but the ability to distinguish inputs to keys in the same column is reduced
Solution Approach 1:
The system applies different detection strategies to different local regions of the keyboard based on finger position and bending degree. Instead of using a uniform key column matching approach, the system determines key columns locally based on the specific finger's position and posture, enabling precise distinction between keys in the same column while maintaining overall keyboard layout stability
Solution Approach 2:
The system changes key column matching parameters based on finger position and bending degree. When a finger is detected at a specific position with a certain bending degree, the system adjusts which key column the finger corresponds to, allowing accurate key identification while preserving the stable virtual keyboard structure
3Device complexity
If the virtual keyboard layout is fixed, then the system is simple to implement, but the layout cannot be changed or adapted
Solution Approach 1:
The virtual keyboard layout transitions from a completely fixed structure to a dynamically adaptable structure. The system maintains a base virtual keyboard layout for simplicity but enables dynamic reconfiguration of key column and key row assignments based on detected finger positions and device posture, achieving both implementation simplicity and layout flexibility
Solution Approach 2:
The virtual keyboard system serves multiple functions: it operates as a standard fixed layout keyboard for common cases while simultaneously adapting to different device orientations and finger positions. This multi-functionality allows the same keyboard to serve various typing scenarios without requiring multiple separate keyboard implementations
Data Source
AI summary
Disclosed is an electronic device configured to obtain a second image, by cropping a first image obtained through a camera, detect at least one finger object in the second image, the at least one finger object corresponding to at least one finger, determine at least one key column corresponding to the at least one finger object among a plurality of key columns of a virtual keyboard by matching the plurality of key columns of the virtual keyboard to a plurality of regions of the second image, and identifying at least one region corresponding to at least one position of the at least one finger object among the plurality of regions of the second image, determine at least one key row corresponding to the at least one finger object among a plurality of key rows of the virtual keyboard, identify, based on the determined at least one key column and the determined at least one key row, at least one virtual key corresponding to the at least one finger object among a plurality of virtual keys of the virtual keyboard, and identify an input of the identified at least one virtual key, based on detecting a typing movement of the at least one finger object.


