Curve-fitting approach to touch gesture finger pitch parameter extraction
View Patent ↗Systems and methods for implementing a touch user interface using at least one at least one edge detection algorithm to produce edge data that is in turn provided to at least one curve-fitting algorithm to produce curve parameter data. The curve parameter data in turn provided to at least one calculation algorithm to produce interpreted data, wherein the interpreted data comprises user interface information responsive to the human touch made by the user to the touch surface. In various implementations the touch sensor can include a capacitive matrix, pressure sensor array, LED array, arrays of on-off contact sensors, or a video camera. The resulting arrangement can be configured to detect touch gestures comprising changes in finger pitch angles and roll angles.
1. A system for implementing a touch user interface, the system comprising:
a touch sensor providing tactile sensing data responsive to human touch made by a user to a touch surface disposed on the touch sensor;
at least one processor for performing calculations on the tactile sensing data and from this producing processed sensor data;
at least one edge detection algorithm for performing operations on the processed sensor data to produce edge data;
at least one curve-fitting algorithm for performing operations on the processed sensor data to produce curve parameter data; and
at least one calculation algorithm for performing operations on the curve parameter data to produce interpreted data:
wherein the interpreted data comprises user interface information responsive to the human touch, and
wherein the system is configured to be responsive to a touch-gesture comprising a change in the pitch angle of a finger.
2. The system of claim 1 . wherein the touch sensor comprises a capacitive matrix.
3. The system of claim 1 , wherein the touch sensor comprises a pressure sensor array.
4. The system of claim 1 , wherein the touch sensor comprises a light emitting diode (LED) array.
5. The system of claim 1 , wherein the touch sensor comprises a video camera.
6. The system of claim 1 , wherein the edge detection algorithm implements a Canny edge detection procedure.
7. The system of claim 1 , wherein the curve-fitting algorithm includes a polynomial regression.
8. The system of claim 1 , wherein the curve-fitting algorithm implements a superellipse curve fit.
9. The system of claim 1 , wherein the interpreted data comprises a calculation of at least one numerical quantity whose value is responsive to the touch-based gesture made by the user.
10. The system of claim 1 , wherein the system is Further configured to he responsive to a touch-based gesture comprises a change in the roll angle of the finger.
11. A method for implementing a touch user interface, the method comprising:
receiving tactile sensing data from a touch surface disposed on a touch sensor, the touch sensor providing the tactile sensing data responsive to human touch made by a user to the touch surface;
providing the tactile sensing data to at least one processor for performing calculations on the tactile sensing data;
processing the tactile sensing data with the at least one processor to produce processed sensor data;
providing the processed sensor data to at least one edge detection algorithm for performing operations on the processed sensor data to produce edge data;
providing the edge data to at least one curve-fitting algorithm for performing operations on the processed sensor data to produce curve parameter data;
providing the curve parameter data to at least one calculation algorithm for performing operations on the curve parameter data to produce interpreted data, and performing operations on the processed sensor data with an artificial neural network to produce interpreted data:
wherein the interpreted data comprises user interface information responsive to the human touch, and
wherein the touch-gesture comprises a change in the pitch angle of a finger.
12. The method of claim 11 , wherein the touch sensor comprises a capacitive matrix.
13. The method of claim 11 , wherein the touch sensor comprises a pressure sensor array.
14. The method of claim 11 , wherein the touch sensor comprises a light emitting diode (LED) array.
15. The method of claim 11 , wherein the touch sensor comprises a video camera.
16. The method of claim 11 , wherein the edge detection algorithm implements a Canny edge detection procedure.
17. The method of claim 11 , wherein the curve-fitting algorithm includes a polynomial regression.
18. The method of claim 11 , wherein the curve-fitting algorithm implements a superellipse curve fit.
19. The method of claim 11 , wherein the interpreted data comprises a calculation of at least one numerical quantity whose value is responsive to the touch-based gesture made by the user.
20. The method of claim 11 , wherein the method is further configured to be responsive to a touch-based gesture comprises a change in the roll angle of the finger.