MULTI-TOUCH HAND POSITION OFFSET COMPUTATION

• US 20070078919A1
• Filed: 11/14/2006
• Published: 04/05/2007
• Est. Priority Date: 01/26/1998
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: FingerWorks Limited (Apple Inc.)
• Inventors: Westerman, Wayne, Elias, John
• Granted Patent: US 8,674,943 B2
• Time in Patent Office: Days
• US Class Current: 708/200
• CPC Class Codes: G06F 18/24137 Distances to cluster centroïds
• CPC Class Codes: G06F 2203/04101 2.5D-digitiser, i.e. digitiser detecting the X/Y position of the input means, finger or stylus, also when it does not touch, but is proximate to the digitiser's interaction surface and also measures the distance of the input means within a short range in the Z direction, possibly with a separate measurement setup
• CPC Class Codes: G06F 2203/04104 Multi-touch detection in digitiser, i.e. details about the simultaneous detection of a plurality of touching locations, e.g. multiple fingers or pen and finger
• CPC Class Codes: G06F 2203/04106 Multi-sensing digitiser, i.e. digitiser using at least two different sensing technologies simultaneously or alternatively, e.g. for detecting pen and finger, for saving power or for improving position detection
• CPC Class Codes: G06F 2203/04808 Several contacts: gestures triggering a specific function, e.g. scrolling, zooming, right-click, when the user establishes several contacts with the surface simultaneously; e.g. using several fingers or a combination of fingers and pen
• CPC Class Codes: G06F 3/0235 using chord techniques G06F3/0234 takes precedence
• CPC Class Codes: G06F 3/041 Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
• CPC Class Codes: G06F 3/0412 Digitisers structurally integrated in a display
• CPC Class Codes: G06F 3/04166 Details of scanning methods, e.g. sampling time, grouping of sub areas or time sharing with display driving Synchronisation with the driving of the display or the backlighting unit to avoid interferences generated internally G06F3/04184
• CPC Class Codes: G06F 3/04186 Touch location disambiguation
• CPC Class Codes: G06F 3/0446 using a grid-like structure of electrodes in at least two directions, e.g. using row and column electrodes
• CPC Class Codes: G06F 3/0447 Position sensing using the local deformation of sensor cells
• CPC Class Codes: G06F 3/04815 Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06F 3/0485 Scrolling or panning
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06V 30/19173 Classification techniques
• CPC Class Codes: G06V 30/1983 Syntactic or structural pattern recognition, e.g. symbolic string recognition
• CPC Class Codes: G06V 40/107 : Static hand or arm
• CPC Class Codes: H03K 17/9622 : using a plurality of detectors, e.g. keyboard
• CPC Class Codes: H03K 2217/960725 : Charge-transfer

Abstract

Apparatus and methods are disclosed for simultaneously tracking multiple finger and palm contacts as hands approach, touch, and slide across a proximity-sensing, multi-touch surface. Identification and classification of intuitive hand configurations and motions enables unprecedented integration of typing, resting, pointing, scrolling, 3D manipulation, and handwriting into a versatile, ergonomic computer input device.

Claims

1. A method of computing a hand position offset from measured positions of individual hand parts on or near a multi-touch surface, the method comprising:

identifying each hand part; and

computing a hand position offset as an average of a difference between a measured position of each hand part and a default position of the hand part.

2. The method of claim 1 further comprising:

establishing an offset weighting for each hand part; and

wherein computing the hand position offset comprises computing the hand position offset as a weighted average of a difference between a measured position of each hand part and a default position of the hand part.

3. The method of claim 1 further comprising:

computing a finger position offset by subtracting a predetermined default position of the hand part and the hand position offset from a measured position of the hand part.

4. The method of claim 1 further comprising:

computing an average of individual hand part velocities;

predicting current hand offset from one or more previous offsets and the computed average velocity; and

updating the predicted hand offset to an average of the predicted offset and the computed offsets.

5. The method of claim 4 wherein one or more of the computed averages are weighted averages.

6. The method of claim 4 further comprising:

computing a confidence in hand part identifications; and

giving increasing weight to the computed offset used in updating the predicted hand offset as the computed confidence increases.

7. The method of claim 6 wherein one or more of the computed averages are weighted averages.

8. The method of claim 3 further comprising:

computing an average of individual hand part velocities;

predicting current hand and finger offsets from one or more previous offsets and the computed average velocity; and

updating the predicted hand and finger offsets to an average of the predicted offset and the computed offsets.

9. The method of claim 8 wherein one or more of the computed averages are weighted averages.

10. The method of claim 8 further comprising:

computing a confidence in hand part identifications; and

giving increasing weight to the computed offsets used in updating the predicted hand and finger offsets as the computed confidence increases.

11. The method of claim 10 wherein one or more of the computed averages are weighted averages.