IDENTIFYING CONTACTS ON A TOUCH SURFACE

• US 20060238522A1
• Filed: 07/03/2006
• Published: 10/26/2006
• Est. Priority Date: 01/26/1998
• Status: Abandoned Application

• Current Assignee: Apple Inc.
• Original Assignee: FingerWorks Inc (Apple Inc.)
• Inventors: WESTERMAN, WAYNE, ELIAS, JOHN G.
• Application Number:
  US11/428,522
• Publication Number:
  US 20060238522A1
• Time in Patent Office: Days
• US Class Current: 345/173
• 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 for tracking and identifying contacts in a sequence of proximity images, the method comprising:

segmenting each proximity image into a plurality of groups of electrodes which indicate significant proximity, wherein at least one group represents proximity of a distinguishable contact;

extracting from at least one group of electrodes one or more parameters selected from the group consisting of;

total proximity, position, shape, size, and orientation parameters from each group of electrodes.

2. The method of claim 1 further comprising tracking a path of one or more groups through successive proximity images.

3. The method of claim 2 wherein tracking group paths through successive proximity images further comprises detection of one or more path endpoints corresponding to a contact touchdown or liftoff.

4. The method of claim 2 or 3 further comprising computing at least one of velocity and position vectors along each path.

5. The method of claim 4 further comprising assigning a contact identity to at least one group by incorporating at least one of:

relative path positions and velocities, individual contact features, and previous estimates contact positions.

6. The method of claim 5 further comprising maintaining estimates of contact positions from trajectories of paths currently assigned to the contacts.

7. The method of claim 6 wherein the estimates of contact positions provide feedback to segmentation and contact identification of future images.

8. The method of claim 1, 2, or 3 further comprising assigning a contact identity to at least one group by incorporating at least one of:

relative path positions and velocities, individual contact features, and previous estimates contact positions.

9. The method of claim 8 further comprising maintaining estimates of contact positions from trajectories of paths currently assigned to the contacts.

10. The method of claim 9 wherein the estimates of contact positions provide feedback to segmentation and contact identification of future images.

11. A method for segmenting hand contacts in a sequence of proximity images, the method comprising:

creating a smoothed copy of the most recent proximity image;

locating one or more locally maximum pixels in the smoothed proximity image; and

searching outward from each local maximum pixel for corresponding contact boundary pixels using boundary tests that depend on one or more expected contact properties.

12. The method of claim 11 further comprising forming groups from those pixels surrounding each local maximum pixel up to and including the corresponding contact boundary pixels.

13. The method of claim 12 further comprising combining groups of pixels that partially overlap.

14. The method of claim 12 further comprising extracting group positions and features by fitting an ellipse to each group of pixels.

15. The method of claim 13 further comprising extracting group positions and features by fitting an ellipse to each group of pixels.