U.S. patent application number 12/238342 was filed with the patent office on 2009-07-09 for motion component dominance factors for motion locking of touch sensor data.
This patent application is currently assigned to Apple Inc.. Invention is credited to Wayne Carl WESTERMAN.
Application Number | 20090174676 12/238342 |
Document ID | / |
Family ID | 40481783 |
Filed Date | 2009-07-09 |
United States Patent
Application |
20090174676 |
Kind Code |
A1 |
WESTERMAN; Wayne Carl |
July 9, 2009 |
MOTION COMPONENT DOMINANCE FACTORS FOR MOTION LOCKING OF TOUCH
SENSOR DATA
Abstract
An image jaggedness filter is disclosed that can be used to
detect the presence of ungrounded objects such as water droplets or
coins, and delay periodic baseline adjustments until these objects
are no longer present. To do otherwise could produce inaccurate
normalized baseline sensor output values. The application of a
global baseline offset is also disclosed to quickly modify the
sensor offset values to account for conditions such as rapid
temperature changes. Background pixels not part of any touch
regions can be used to detect changes to no-touch sensor output
values and globally modify the sensor offset values accordingly.
The use of motion dominance ratios and axis domination confidence
values is also disclosed to improve the accuracy of locking onto
dominant motion components as part of gesture recognition.
Inventors: |
WESTERMAN; Wayne Carl; (San
Francisco, CA) |
Correspondence
Address: |
APPLE C/O MORRISON AND FOERSTER ,LLP;LOS ANGELES
555 WEST FIFTH STREET SUITE 3500
LOS ANGELES
CA
90013-1024
US
|
Assignee: |
Apple Inc.
Cupertino
CA
|
Family ID: |
40481783 |
Appl. No.: |
12/238342 |
Filed: |
September 25, 2008 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61019222 |
Jan 4, 2008 |
|
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Current U.S.
Class: |
345/173 |
Current CPC
Class: |
G06K 9/50 20130101; G06T
7/337 20170101; G06F 3/04883 20130101; G06F 3/0418 20130101 |
Class at
Publication: |
345/173 |
International
Class: |
G06F 3/041 20060101
G06F003/041 |
Claims
1. A method for processing touch images using separable control,
comprising: computing a scale_dominance_ratio (SDR) value and a
rotate_dominance_ratio (RDR) value as a function of identified
contacts on a touch sensor panel, the SDR and RDR values
representing dominance values of a scaling component and a
rotational component, respectively, of motion associated with the
contacts; utilizing the SDR and RDR values to determine a motion
component to lock onto when performing gesture identification.
2. The method of claim 1, further comprising computing the SDR and
RDR values as a function of fingers and thumbs associated with the
contacts.
3. The method of claim 1, further comprising: capturing multiple
images of touch; extracting motion components from the captured
images of touch; computing a smooth translation speed, a smooth
rotate speed, and a smooth scale speed from the motion components;
and utilizing the smooth translation speed, the smooth rotate
speed, and the smooth scale speed along with the SDR and RDR values
to determine the motion component to lock into when performing
gesture identification.
4. The method of claim 3, the motion components comprising an
x-direction velocity (Vx), a y-direction velocity (Vy), a
rotational velocity (Vr), and a scaling velocity (Vs).
5. The method of claim 4, further comprising applying a
mathematical low pass filter (LPF) to compute the smooth
translation speed, the smooth rotate speed, and the smooth scale
speed as: TABLE-US-00003 Smooth_translation_speed = (LPF(Vx).sup.2
+ LPF(Vy).sup.2).sup.0.5; Smooth_rotate_speed = LPF(Vr); and
Smooth_scale_speed = LPF(Vs).
6. The method of claim 2, further comprising setting the SDR and
RDR values to 2.5 if a thumb is detected as one of the identified
contacts.
7. The method of claim 2, further comprising setting the SDR and
RDR values below 2.5 if two or more fingers but no thumbs are
detected as the identified contacts.
8. The method of claim 7, further comprising setting the SDR to
about 0.25 if a finger separation between at least two of the
fingers is between 0 and about 3 cm, setting the SDR between about
0.25 and about 1.25 if the finger separation is between about 3 cm
and about 6 cm, and setting the SDR to between about 1.25 and about
2.5 if the finger separation is greater than about 6 cm.
9. The method of claim 8, further comprising setting the SDR to
0.25 even if the finger separation is greater than about 3 cm if a
downward translation is detected along with a scale
contraction.
10. The method of claim 3, further comprising: locking onto a
translation component and clipping the scaling component of the
motion associated with the contacts if the smooth translation speed
is greater than the SDR multiplied by the smooth scale speed; and
locking onto the translation component and clipping the rotational
component of the motion associated with the contacts if the smooth
translation speed is greater than the RDR multiplied by the smooth
rotate speed.
11. The method of claim 10, further comprising computing an axis
domination confidence value as a representation of an
unambiguousness of the motion component to lock onto as: if the
smooth translation speed is less than the smooth scale speed plus
the smooth rotate speed, then axis_domination _confidence = 1 -
smooth translation speed ( smooth_scale _speed + smooth_rotate
_speed ) , otherwise , axis_domination _confidence = 1 - (
smooth_scale _speed + smooth_rotate _speed ) smooth translation
speed . ##EQU00003##
12. The method of claim 11, further comprising delaying the locking
onto the motion component by an amount proportional to the axis
domination confidence value.
13. The method of claim 11, further comprising multiplying the axis
domination confidence value by any non-clipped motion components to
delay a locking decision.
14. A computer-readable storage medium storing program code for
processing touch images using separable control, the program code
for causing performance of a method comprising: computing a
scale_dominance_ratio (SDR) value and a rotate_dominance_ratio
(RDR) value as a function of identified finger and thumb contacts
on a touch sensor panel, the SDR and RDR values representing
dominance values of a scaling component and a rotational component,
respectively, of motion associated with the contacts; utilizing the
SDR and RDR values to determine a motion component to lock onto
when performing gesture identification, the motion components
including an x-direction velocity (Vx), a y-direction velocity
(Vy), a rotational velocity (Vr), and a scaling velocity (Vs).
15. The computer-readable storage medium of claim 14, the program
code further for causing performance of a method comprising:
capturing multiple images of touch; extracting the motion
components from the captured images of touch; computing a smooth
translation speed, a smooth rotate speed, and a smooth scale speed
from the motion components; and utilizing the smooth translation
speed, the smooth rotate speed, and the smooth scale speed along
with the SDR and RDR values to determine the motion component to
lock into when performing gesture identification.
16. The computer-readable storage medium of claim 15, the program
code further for causing performance of a method comprising
applying a mathematical low pass filter (LPF) to compute the smooth
translation speed, the smooth rotate speed, and the smooth scale
speed as: TABLE-US-00004 Smooth_translation_speed = (LPF(Vx).sup.2
+ LPF(Vy).sup.2).sup.0.5; Smooth_rotate_speed = LPF(Vr); and
Smooth_scale_speed = LPF(Vs).
17. The computer-readable storage medium of claim 14, the program
code further for causing performance of a method comprising setting
the SDR and RDR values to 2.5 if a thumb is detected as one of the
identified contacts.
18. The computer-readable storage medium of claim 14, the program
code further for causing performance of a method comprising setting
the SDR and RDR values below 2.5 if two or more fingers but no
thumbs are detected as the identified contacts.
19. The computer-readable storage medium of claim 18, the program
code further for causing performance of a method comprising setting
the SDR to about 0.25 if a finger separation between at least two
of the fingers is between 0 and about 3 cm, setting the SDR between
about 0.25 and about 1.25 if the finger separation is between about
3 cm and about 6 cm, and setting the SDR to between about 1.25 and
about 2.5 if the finger separation is greater than about 6 cm.
20. The computer-readable storage medium of claim 19, the program
code further for causing performance of a method comprising setting
the SDR to 0.25 even if the finger separation is greater than about
3 cm if a downward translation is detected along with a scale
contraction.
21. The computer-readable storage medium of claim 15, the program
code further for causing performance of a method comprising:
locking onto a translation component and clipping the scaling
component of the motion associated with the contacts if the smooth
translation speed is greater than the SDR multiplied by the smooth
scale speed; and locking onto the translation component and
clipping the rotational component of the motion associated with the
contacts if the smooth translation speed is greater than the RDR
multiplied by the smooth rotate speed.
22. The computer-readable storage medium of claim 21, the program
code further for causing performance of a method comprising
computing an axis domination confidence value as a representation
of an unambiguousness of the motion component to lock onto as: if
the smooth translation speed is less than the smooth scale speed
plus the smooth rotate speed, then axis_domination _confidence = 1
- smooth translation speed ( smooth_scale _speed + smooth_rotate
_speed ) , otherwise , axis_domination _confidence = 1 - (
smooth_scale _speed + smooth_rotate _speed ) smooth translation
speed . ##EQU00004##
23. The computer-readable storage medium of claim 22, the program
code further for causing performance of a method comprising
delaying the locking onto the motion component by an amount
proportional to the axis domination confidence value.
24. The computer-readable storage medium of claim 22, the program
code further for causing performance of a method comprising
multiplying the axis domination confidence value by any non-clipped
motion components to delay a locking decision.
25. A mobile telephone including a computer-readable storage medium
storing program code for processing touch images using separable
control, the program code for causing performance of a method
comprising: computing a scale_dominance_ratio (SDR) value and a
rotate_dominance_ratio (RDR) value as a function of identified
contacts on a touch sensor panel, the SDR and RDR values
representing dominance values of a scaling component and a
rotational component, respectively, of motion associated with the
contacts; utilizing the SDR and RDR values to determine a motion
component to lock onto when performing gesture identification.
26. A media player including a computer-readable storage medium
storing program code for processing touch images using separable
control, the program code for causing performance of a method
comprising: computing a scale_dominance_ratio (SDR) value and a
rotate_dominance_ratio (RDR) value as a function of identified
contacts on a touch sensor panel, the SDR and RDR values
representing dominance values of a scaling component and a
rotational component, respectively, of motion associated with the
contacts; utilizing the SDR and RDR values to determine a motion
component to lock onto when performing gesture identification.
27. A personal computer including a computer-readable storage
medium storing program code for processing touch images using
separable control, the program code for causing performance of a
method comprising: computing a scale_dominance_ratio (SDR) value
and a rotate_dominance_ratio (RDR) value as a function of
identified contacts on a touch sensor panel, the SDR and RDR values
representing dominance values of a scaling component and a
rotational component, respectively, of motion associated with the
contacts; utilizing the SDR and RDR values to determine a motion
component to lock onto when performing gesture identification.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Patent Application No. 61/019,222 filed on Jan. 4, 2008, the
contents of which are incorporated herein by reference in their
entirety for all purposes.
FIELD OF THE INVENTION
[0002] This relates to touch sensor panels used as input devices
for computing systems, and more particularly, to the normalization
and post-processing of touch sensor data.
BACKGROUND OF THE INVENTION
[0003] Many types of input devices are presently available for
performing operations in a computing system, such as buttons or
keys, mice, trackballs, touch sensor panels, joysticks, touch
screens and the like. Touch screens, in particular, are becoming
increasingly popular because of their ease and versatility of
operation as well as their declining price. Touch screens can
include a touch sensor panel, which can be a clear panel with a
touch-sensitive surface. The touch sensor panel can be positioned
partially or completely in front of a display screen, or integrated
partially or entirely within the display screen, so that at least a
portion of the touch-sensitive surface covers at least a portion of
the viewable area of the display screen. Touch screens can allow a
user to make selections and move a cursor by simply touching the
display screen via a finger or stylus. In general, the touch screen
can recognize the touch and position of the touch on the display
screen, and the computing system can interpret the touch and
thereafter perform an action based on the touch event.
[0004] Touch sensor panels can be capable of detecting either
single-touch events or multiple touch events, an example of which
is described in Applicant's co-pending U.S. application Ser. No.
11/649,998 entitled "Proximity and Multi-Touch Sensor Detection and
Demodulation," filed on Jan. 3, 2007, the contents of which are
incorporated by reference herein in their entirety for all
purposes.
[0005] To provide a more uniform response from the touch sensor
panel given the same amount of touch, the sensor output values can
be calibrated or normalized by using offset values to compensate
the raw no-touch output values for each sensor in the panel so that
all sensor output values are normalized to approximately the same
value. A periodic local baseline offset adjustment algorithm can
then be employed to locally update the sensor offset values to
account for variables such as temperature drift. However, when
ungrounded objects such as water droplets or coins are present on
the touch sensor panel, the periodic local baseline offset
adjustment algorithm can generate inaccurate normalized results.
Furthermore, factors such as temperature changes can rapidly skew
the normalized sensor output values. In addition, when processing
touch data to recognize gestures, it can be difficult to clearly
identify and lock onto a particular dominant motion component as a
preliminary step in recognizing a particular gesture.
SUMMARY OF THE INVENTION
[0006] This relates to an image jaggedness filter that can be used
to detect the presence of ungrounded objects such as water droplets
or coins on a touch sensor panel, and delay periodic local offset
adjustments until these objects have largely disappeared. To do
otherwise could produce inaccurate normalized sensor output values.
This also relates to the application of a global baseline offset to
quickly normalize the sensor output values to account for
conditions such as rapid temperature changes. Background pixels not
part of any touch regions can be used to detect changes to no-touch
sensor output values and compute a global baseline offset
accordingly. This also relates to the use of motion dominance
ratios and axis domination confidence values to improve the
accuracy of locking onto dominant motion components as part of
gesture recognition.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIGS. 1a-1c illustrate an exemplary periodic local baseline
adjustment for a single row of pixels in a touch sensor panel
according to embodiments of the invention.
[0008] FIG. 2a illustrates an exemplary touch sensor panel having
water droplets on its touch surface and the resulting touch image
having a high spatial frequency.
[0009] FIG. 2b illustrates an exemplary flow diagram of the use of
the image jaggedness filter according to one embodiment of this
invention.
[0010] FIG. 3 illustrates an exemplary image of touch on touch
sensor panel showing how a global baseline offset can be determined
according to one embodiment of this invention.
[0011] FIG. 4a illustrates the computation of an exemplary periodic
global baseline offset adjustment value for a single row of pixels
(sensors) A-G in a touch sensor panel according to embodiments of
the invention.
[0012] FIG. 4b illustrates an exemplary plot of the overall offset
value for a single sensor over time including the total
contributions of a local baseline offset and the contribution of a
global baseline offset according to one embodiment of this
invention.
[0013] FIG. 4c illustrates an exemplary flowchart or algorithm for
implementing the global baseline offset algorithm according to
embodiments of the invention.
[0014] FIG. 4d illustrates an exemplary plot of the overall offset
value for a single sensor over time wherein the global baseline
offset value is applied to the sensor offset value gradually
according to embodiments of the invention.
[0015] FIG. 5 illustrates an exemplary motion component dominance
algorithm that can be implemented by a processor executing firmware
according to embodiments of the invention.
[0016] FIG. 6 illustrates an exemplary algorithm for computing an
axis_domination_confidence value that can be implemented by a
processor executing firmware according to embodiments of the
invention.
[0017] FIG. 7 illustrates an exemplary computing system operable
with a touch sensor panel to implement the image jaggedness filter,
global baseline offset, and motion component dominance factors
according to one embodiment of this invention.
[0018] FIG. 8a illustrates an exemplary mobile telephone that can
include a touch sensor panel and computing system for implementing
the image jaggedness filter, global baseline offset, and motion
component dominance factors according to one embodiment of this
invention.
[0019] FIG. 8b illustrates an exemplary digital media player that
can include a touch sensor panel and computing system for
implementing the image jaggedness filter, global baseline offset,
and motion component dominance factors according to one embodiment
of this invention.
[0020] FIG. 8c illustrates an exemplary personal computer that can
include a touch sensor panel and computing system for implementing
the image jaggedness filter, global baseline offset, and motion
component dominance factors according to one embodiment of this
invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
[0021] In the following description of preferred embodiments,
reference is made to the accompanying drawings in which it is shown
by way of illustration specific embodiments in which the invention
can be practiced. It is to be understood that other embodiments can
be used and structural changes can be made without departing from
the scope of the embodiments of this invention.
[0022] This relates to an image jaggedness filter that can be used
to detect the presence of ungrounded objects such as water droplets
or coins, and delay periodic local baseline offset adjustments
until these objects have largely disappeared. To do otherwise could
produce inaccurate normalized sensor output values. This also
relates to the application of a global baseline offset to quickly
modify the sensor offset values to account for conditions such as
rapid temperature changes. Background pixels not part of any touch
regions can be used to detect changes to no-touch sensor output
values and compute the global baseline offset accordingly. This
also relates to the use of motion dominance ratios and axis
domination confidence values to improve the accuracy of locking
onto dominant motion components as part of gesture recognition.
Image Jaggedness Filter for Baseline Calculations
[0023] To provide a more uniform response from the touch sensor
panel given the same amount of touch, touch sensor panel output
values can be calibrated using offset values to adjust the raw
no-touch output values for each sensor in the panel so that all
touch sensor panel output values are normalized to approximately
the same value. However, even with normalized sensor outputs,
temperature drift and other factors can cause the sensor output
values to change, which will tend to skew the normalized baseline.
To account for these gradual changes to the normalized sensor
output values, a periodic local baseline offset adjustment
algorithm can be employed.
[0024] FIGS. 1a-1c illustrate an exemplary periodic local baseline
adjustment for a single row of pixels (sensors) A-G in a touch
sensor panel according to embodiments of the invention. Although
not shown, it should be understood that each row in the touch
sensor panel can also be subject to this periodic local baseline
adjustment. The periodic local baseline offset adjustment algorithm
can increment or decrement individual sensor offset values by one
count or unit, or some small value to provide periodic fine-tuning
of the offsets to track temperature drift or other shifts in the
sensor output values.
[0025] As shown in FIG. 1a, to perform this periodic local baseline
offset adjustment, a no-touch scan of the sensor panel is performed
after a dynamic adjustment time interval has passed, and raw sensor
output values 108 are obtained. The adjustment time interval is
generally much longer than the frame rate (the time it takes to
scan the entire sensor panel one time). Previously computed offset
values for each sensor (see 110-A through 110-G) are then
subtracted from the measured raw sensor output values 108 to
normalize them. Ideally, as shown in FIG. 1a, the subtraction
results in all normalized sensor output values being equal to the
same baseline value 112.
[0026] However, as shown in FIG. 1b, if some of the no-touch
measured raw sensor output values 114 shift due to a change in some
condition such as a temperature increase, for example, after
subtraction of the offset values 110-A through 110-G, some of the
normalized sensor output values may be equal to some value other
than baseline value 112, such as value 116 in FIG. 1b. To adjust
for this shift according to embodiments of the invention, all
sensors having normalized sensor output values that are positive
and negative as compared to the baseline 112 are identified. (In
the example of FIG. 1b, the normalized sensor values for sensors
B-E and G are positive.) For any sensors with normalized sensor
output values that are positive, their corresponding offset values
are incremented by P, where P may be one count, or a small value,
or a percentage of the positive value. In the example of FIG. 1b, P
represents the full difference between value 116 and the original
baseline 112, but it should be understood that if P represents less
than the full difference between value 116 and the original
baseline 112, multiple periodic local baseline offset adjustments
can eventually take up the full difference. Similarly, for any
sensors with normalized sensor output values that are negative,
their corresponding offset values are decremented by Q, where Q may
be one count, or a small value, or a percentage of the negative
value. The algorithm waits the duration of an adjustment period
before scanning the panel again.
[0027] As shown in FIG. 1c, after the sensor offset values for
sensors B-E and G have been adjusted, the normalized sensor output
values should be closer to the original baseline 112. In the
example of FIG. 1c, because the offset adjustment value P
represented the full difference between value 116 and the original
baseline 112, the normalized sensor output values equal the
original baseline 112.
[0028] Despite this normalization, in multi-touch sensor panels,
certain pixels can generate false, erroneous or otherwise distorted
readings when two or more simultaneous touch events are generated
by the same poorly grounded object. Compensation of these distorted
readings (so-called "negative pixels") is described in U.S.
application Ser. No. 11/963,578 entitled "Negative Pixel
Compensation," the contents of which are incorporated by reference
herein in their entirety for all purposes. To compensate for these
distorted readings, a predicted negative pixel value can first be
computed as an indicator of pixels that are likely to be distorted.
The predicted negative pixel value for any particular pixel can be
computed by summing up the touch output values for pixels in the
drive line of the particular pixel being considered, summing up the
touch output values for pixels in the sense line of the particular
pixel being considered, and then multiplying these two sums. A
scaled function of the predicted negative pixel value can then be
added to the measured touch output value for the pixel to
compensate for artificially negative readings.
[0029] However, due to physical design changes, state-of-the-art
touch sensor panels can have a greater incidence of negative pixels
than previous touch sensor panels. In trackpad embodiments, for
example, negative pixels can appear more frequently due to the
expected frequent usage of unplugged notebook computers, which can
cause a higher incidence of touches by ungrounded objects. Thus,
for a given image of touch, there can be a higher sum of negative
and positive pixels than in previous designs.
[0030] Water droplets on a touch sensor panel can also appear as
ungrounded objects. On trackpads, where user fingers and palms are
often touching (sometimes inadvertently) the panel, water droplets
can easily get smeared. Therefore, if the possible presence of
water droplets can be detected, it would be preferable to hold off
on any periodic local baseline offset adjustment until the water
has dried off, because of the likely existence of corrupting
negative pixels.
[0031] To suppress periodic local baseline offset adjustments in
the presence of water droplets, extra filters can first be employed
to detect the presence of water droplets. To detect water droplets,
a jaggedness/irregularity filter can be used, as described in U.S.
application Ser. No. 11/619,490 entitled "Irregular Input
Identification" and U.S. application Ser. No. 11/756,211 entitled
"Multi-touch Input Discrimination," both of which are incorporated
by reference herein in their entirety for all purposes. This
jaggedness/irregularity filter can be used to find touch images
having a high spatial frequency, such as those caused by water
droplets.
[0032] FIG. 2a illustrates an exemplary touch sensor panel 200
having water droplets 202 on its touch surface. The sensors in row
204 can generate touch outputs as shown in plot 106. Plot 206 shows
that water droplets 202, being ungrounded, can generate raw touch
sensor output values having a high spatial frequency (a high
frequency of occurrence of touch images in space), a certain
jaggedness in the captured image, and a number of positive and
negative pixels. Although not shown in FIG. 2, a similar plot can
be obtained for every row and column in touch sensor panel 200.
[0033] FIG. 2b illustrates an exemplary flow diagram of the use of
the image jaggedness filter according to embodiments of the
invention. In FIG. 2, a jaggedness measure can be obtained at 208.
To accomplish this, the jaggedness/irregularity filter as mentioned
above can be applied to all rows and columns to generate a
jaggedness measure for the entire image. In some embodiments, the
jaggedness measure for all rows and columns can be averaged and
normalized. Alternatively, a spatial Fourier transform can be
used.
[0034] If a moderate (relatively even) mix of negative and positive
pixels are found or are within a particular mix threshold at 210,
and a certain jaggedness threshold is exceeded at 212, indicating
the presence of numerous poorly grounded objects such as water
droplets, then the next periodic local baseline offset adjustment
can be skipped at 214. For example, a "moderate" mix of negative
and positive pixels may be defined as having percentages of
negative and positive pixels are within 40% of each other -30% and
70%. All other percentages would not be considered "moderate."
Additionally, if the jaggedness measure is normalized between
[0,1], with "0" being not jagged (no ungrounded objects) and "1"
being completely jagged (many small ungrounded objects), then the
jaggedness threshold could be set to 0.5.
[0035] If the jaggedness threshold is not exceeded at 212, but the
number of positive and negative pixels is changing rapidly at 216
(which can occur when water droplets are evaporating), periodic
local baseline offset adjustments can also be suppressed at 214. To
make this determination of whether the number of positive and
negative pixels are changing rapidly, the sums of the negative and
positive pixels can be passed though a (mathematical) low pass
filter (LFP) that produces an auto-regressive average.
Instantaneous values can then be subtracted from the average. If
the difference is high (greater than a predetermined threshold,
such as the instantaneous value being more than 25% different from
the computed average), this indicates a large change in the number
of negative or positive pixels sufficient to suppress periodic
local baseline offset adjustments. On the other hand, if the number
of positive and negative pixels is not changing rapidly at 216,
then the next periodic local baseline offset adjustment can occur
as scheduled at 218 (including the suppression of an initial
baseline capture if fingers are detected at startup, as disclosed
in U.S. application Ser. No. 11/650,112 entitled "Periodic Sensor
Panel Baseline Adjustment," the contents of which are incorporated
by reference herein in their entirety for all purposes).
[0036] If the mix of negative and positive pixels is not moderate
at 210 (e.g. many more positive pixels than negative pixels, or
vice versa), the jaggedness threshold is not exceeded at 222, and
the mix of negative and positive pixels is changing rapidly at 216,
periodic local baseline offset adjustments can be suppressed at
214. However, if the mix of negative and positive pixels is not
changing rapidly at 216, periodic local baseline offset adjustments
can be performed at 218.
[0037] After enough water evaporates, no significant number of
negative pixels may remain, but some positive pixels may remain. If
the positive pixels are scattered spatially, they can still cause
the jaggedness measure to be above the threshold. Note that the
jaggedness algorithm may only recognize that the jaggedness measure
has exceeded a threshold--it does not see actual negative and
positive pixels, so it cannot determine that there are few negative
pixels remaining. Thus, if the mix of negative and positive pixels
is not moderate at 210, but the jaggedness threshold is exceeded at
222, periodic local baseline offset adjustments can be performed at
218. In addition, to compensate for this effect, the
increment/decrement rate of the adaptation algorithm can be sped
up, so that the positive pixels are compensated more quickly and
the effect is reduced.
Global Baseline Offset
[0038] As described above, there are situations in which it can be
preferable to delay periodic local baseline offset adjustments so
that ungrounded touches do not cause erroneous adjustments to the
sensor offset values. Additionally, with conventional keyboards
having trackpads, inadvertent touch events can be commonplace while
the keyboard is being utilized, presenting another situation where
it can be preferable to keep the adaptation rate slower so that
patches due to hovering or inadvertent touches do not get
incorporated into the sensor offset values. However, it can still
desirable to quickly compensate for temperature or other global
effects.
[0039] Therefore, in addition to the periodic local baseline offset
adjustment algorithm described above that can cause sensor offset
values to be incrementally adapted or changed on a pixel-by-pixel
(local) basis, in other embodiments of the invention a global
baseline offset can be applied to the offset values for all pixels.
The global baseline offset can be used to effect changes much more
quickly than the periodic local baseline offset adjustment
algorithm to compensate for large temperature changes or the
effects of other global conditions. In some embodiments, the full
amount of this global baseline offset can be immediately applied to
the offset values for all pixels. In other embodiments, the offset
values for all pixels can be incremented or decremented gradually
over time (but more often than the individual pixels can be
incremented or decremented using local baseline offset
adjustments), until the full amount of the global baseline offset
has been applied.
[0040] FIG. 3 illustrates an exemplary image of touch on touch
sensor panel 300 showing how a global baseline offset value can be
determined according to embodiments of the invention. First, in
some embodiments, unions of adjacent or nearby patches can be
determined (see 302 and 304). To determine which patches should be
grouped together, any number of methods can be used, such as
computing the centroids of the patches and grouping together those
pixels whose centroids are closest together. The union of those
patches can be formed based on the touch sensor output values
within the patches. For example, for any two grouped patches, all
pixels within those two patches having touch sensor output values
above a certain threshold can be considered part of the union.
These union areas can be blocked out from subsequent calculations
so that only background pixels 306 remain. In other embodiments,
unions need not be formed, and only the patches themselves can be
excluded from the background pixels.
[0041] An average of all or a portion of the background pixels 306
can then be computed, and this average can then used to globally
modify the offset values for all pixels in the touch sensor panel.
Because the background pixels 306 are untouched, the average of
their untouched output values can provide an indication of rapid
changes to the pixel outputs due to factors such as temperature.
This average, or some adjustment value that is a function of this
average, can then be added to or subtracted from the current sensor
baseline to compute the global baseline offset value. This global
baseline offset value can then be added to the current offset
values for every pixel in the touch sensor panel to effect a global
adjustment of the offset values. In some embodiments, this global
baseline offset value can be applied immediately to the current
offset values for every pixel. In other embodiments, the current
offset values can be incremented or decremented gradually until the
full global baseline offset values has been applied. To keep the
normalized sensor output values from "running away" (e.g. getting
excessively large or small) due to unintended artifacts of the
algorithm such as an accumulation of roundoff error, the global
baseline offset value can optionally decay to zero over time.
[0042] FIG. 4a illustrates the computation of an exemplary periodic
global baseline offset value for a single row of pixels (sensors)
A-G in a touch sensor panel according to embodiments of the
invention. Although not shown, it should be understood that each
row in the touch sensor panel can be involved in the computation of
this global baseline offset value. In the example of FIG. 4a,
current no-touch (i.e. background) raw sensor output values 408
have risen substantially and in a fairly uniform manner from
previous no-touch raw sensor output values 420 due to a change in
some condition such as a temperature increase. As such, subtracting
of the previous sensor offset values 410-A through 410-G from the
current raw sensor output values 408 results in normalized values
416 well above the original baseline 412, which can create errors
in touch detection and interpretation. To perform a global baseline
offset adjustment on all offset values in the touch sensor panel,
an average of the background pixels can first be computed. In the
example of FIG. 4a, the average is shown at 422. Next, the
difference between this average and the original baseline 412 can
be computed as the global baseline offset value 424. This global
baseline offset value 424 can then be added to the previous sensor
offset values 410-A through 410-G to produce updated sensor offset
values and effect a global adjustment of the offset values.
[0043] FIG. 4b illustrates an exemplary plot of the overall offset
value 400 for a single sensor over time including the total
contributions of a local baseline offset 404 and the contribution
of a global baseline offset 402 according to embodiments of the
invention. In the example of FIG. 4b, the offset value 400, global
baseline offset value 402, and the total contribution of the local
baseline offset value 404 start near zero at 406, indicating that
the raw no-touch sensor output value for that sensor is
approximately equal to the desired baseline value. If a temperature
shift or other environmental condition is detected at 408 resulting
in a rapid increase in the average of the background pixels (e.g.,
a change of more than 25% over the span of a minute), the full
amount of the calculated global baseline offset value 402 can be
immediately added to the sensor offset value, causing the overall
sensor offset value 400 to increase rapidly to a value 410 equal to
the difference between the average of the background pixels and the
original baseline as described above. The global baseline offset
value 402 can then decay back to zero over time at 412 to ensure
that the offset value does not get excessively large or small due
to unintended artifacts of the algorithm.
[0044] However, if the increase in the raw sensor output values
remains, even while the global baseline offset value 402 is
decaying back down to zero, another mechanism is needed to ensure
that an increase to the overall offset value does occur. To
accomplish this, the local baseline offset adjustment algorithm
described above can periodically incrementally increase the overall
offset value 400 as the global baseline offset value 402 is
decaying. Although each increment to the overall offset value 400
made by the local baseline offset adjustment algorithm is small,
the total contribution of the local baseline offset value 404
gradually increases over time, as shown at 414 in FIG. 4b.
[0045] FIG. 4c illustrates an exemplary flowchart or algorithm for
implementing the global baseline offset algorithm as described
above according to embodiments of the invention.
[0046] Although not shown, similar adjustments to the overall
sensor offset value of each pixel can be made in the negative
direction if the average of the background pixels rapidly
decreases.
[0047] FIG. 4d illustrates an exemplary plot of the overall offset
value 400 for a single sensor over time wherein the global baseline
offset value is applied to the sensor offset value gradually
according to embodiments of the invention. In the example of FIG.
4d, the global baseline offset value 402 can be incrementally added
to the sensor offset value, causing the overall sensor offset value
400 to increase gradually to a value 410 equal to the difference
between the average of the background pixels and the original
baseline as described above. It should be noted that although the
global baseline offset value is applied incrementally, the
increment period can be much faster than the local baseline offset
adjustment described above. The global baseline offset value 402
can then decay back to zero over time at 412 to ensure that the
offset value does not get excessively large or small due to
unintended artifacts of the algorithm.
Motion Component Dominance Factors for Motion Locking
[0048] In the processing of touch images, after touch images (e.g.
from two fingers) are captured, identified and tracked over
multiple panel scans, motion components can be extracted. In the
case of two fingers, motion components can include the X component,
the Y component, a scale (zoom) component (the dot product of the
two finger motion vectors), and a rotate component (the cross
product of the two finger motion vectors). The extracted motion
components can provide for two types of control. "Integral control"
is defined herein as providing all four degrees of freedom (the
ability to control all axes at once). "Separable control" is more
limited, and separates motion between either (1) X-Y scrolling as a
set, (2) zoom, or (3) rotate (i.e. one axis).
[0049] FIG. 5 illustrates an exemplary motion component dominance
algorithm 500 that can be implemented by a processor executing
firmware according to embodiments of the invention. After multiple
images of touch are captured at 502, motion components such as the
x-direction velocity (Vx), y-direction velocity (Vy), rotational
velocity (Vr), and scaling velocity (Vs) can be extracted at 504.
To implement separable control, embodiments of the invention can
lock onto the first component (axis) with significant motion, and
ignore the others. For example, if significant X-Y scrolling is
detected first, subsequently detected zooming motions may be
ignored until liftoff of the fingers. To lock onto the first
component with significant motion, a low pass filter (LPF) can be
applied to the computed velocities of the extracted motion
components to compute the following at 506:
TABLE-US-00001 Smooth_translation_speed = (LPF(Vx).sup.2 +
LPF(Vy).sup.2).sup.0.5 Smooth_rotate_speed = LPF(Vr)
Smooth_scale_speed = LPF(Vs)
[0050] Note that the smooth_translation_speed value includes Vx and
Vy because of the desire to lock onto scrolling as a whole, not
just the X and Y components. Of these three values, the dominant
(largest) computed speed can be used, while the others can be
ignored (zeroed or clipped out).
[0051] However, in practice it can be difficult to lock on
properly, because a scroll motion might initially look like a
rotate motion, for example, or vice versa. Therefore, in
embodiments of the invention, the three raw values described above
can be utilized in conjunction with two new parameters,
scale_dominance_ratio (SDR) and rotate_dominance_ratio (RDR), which
can be used to apply weights to the various motion components and
set a balance point for the motions so that a particular component
can be locked onto more accurately. The SDR and RDR values can be
established after the various finger contacts are identified at
508. The SDR and RDR values computed at 510 can be based on whether
the detected contacts are identified as fingers and/or thumbs. For
example, if a thumb is detected, it can be more likely that a user
is using a thumb and finger to perform a scaling (zoom) or rotate
operation rather than a translation or scroll operation, so the SDR
and RDR values can be set to high values (e.g. 2.5) so that the
Smooth_scale_speed or the Smooth_rotate_speed values dominate the
Smooth_translation_speed value.
[0052] However, if two or more fingers are detected, but not a
thumb, it is more likely that a user is using the two fingers to
perform a translation or scroll operation rather than a scaling or
rotate operation, so the SDR and RDR values can be set to lower
values to ensure that the Smooth_translation_speed value dominates.
The multiple-finger, no-thumb SDR value can further be a function
of the horizontal separation of the fingers, because it can be more
likely that a user is performing a translation or scroll operation
when the fingers are close together, but more likely that a user is
performing a two finger scaling operation when the fingers have a
greater separation. Thus, for example, the SDR can be set to 0.25
if the finger separation is between 0 and 3 cm, can vary from 0.25
to 1.25 if the separation is from 3-6 cm, and can be set to 1.25
for separations greater than 6 cm.
[0053] In further embodiments, an exception can be created for the
SDR during a two-finger top-to-bottom translation because of the
tendency for a user's fingers to draw together during the
translation. The movement of the fingers towards each other during
the translation should not be interpreted as a scaling operation.
To prevent this, if a downward translation is detected plus a scale
contraction, then the SDR can be maintained at 0.25, even if the
two finger separation distance is high.
[0054] After the SDR and RDR values are computed at 510, the
following pseudocode can then be implemented at 512, 514, 516 and
518:
TABLE-US-00002 Variables: scale_dominance_ratio (SDR),
rotate_dominance_ratio (RDR) If (smooth_translation_speed > SDR
.times. smooth_scale_speed), then (A) Clip scale (Vx .fwdarw. pass,
Vs .fwdarw. zero) Leave scroll; If (smooth_translation_speed >
RDR .times. smooth_rotate_speed), then (B) Clip rotate (Vx .fwdarw.
pass, Vr .fwdarw. zero) Leave scroll.
[0055] In other embodiments, where the movement of contacts along
with contact identifications provides an ambiguous determination of
which motion component to lock onto, locking onto a particular
motion component can be delayed until enough motion has occurred to
make a more accurate determination. To accomplish this, an
axis_domination_confidence value can be computed to provide a
representation of the unambiguousness of the motion component to be
locked onto.
[0056] FIG. 6 illustrates an exemplary algorithm 600 for computing
an axis_domination_confidence value that can be implemented by a
processor executing firmware according to embodiments of the
invention. If
smooth_translation_speed<(smooth_scale_speed+smooth_rotate_speed)
at 602, then
axis_domination _confidence = 1 - smooth_translation _speed (
smooth_scale _speed + smooth_rotate _speed ) . ##EQU00001##
at 604. Otherwise, at 606,
[0057] axis_domination _confidence = 1 - ( smooth_scale _speed +
smooth_rotate _speed ) smooth_translation _speed . ##EQU00002##
[0058] The axis_domination_confidence value as calculated above can
be normalized to be between [0,1], where values approaching 1
represent a pure translation (and therefore there is high
confidence in locking on to the X-Y motion components) and values
approaching 0 indicate that the translation amount is about equal
to the scale and rotation amount (and therefore low confidence in
locking on to any motion component).
[0059] After the axis_domination_confidence value is computed, in
one embodiment the motion component locking decision can be delayed
by an amount proportional to the inverse of the
axis_domination_confidence value at 608. Thus, if the value is
high, indicating high confidence, there can be little or no delay.
However, if the value is low, indicating low confidence, the
locking decision can be delayed to allow for the motion components
to become less ambiguous.
[0060] In another embodiment, the axis_domination_confidence value
(or the square of this value) can be multiplied by any non-clipped
motion components (see, e.g., equations (A) and (B) above) at 610.
This has the effect of slowing down the ultimate gesture decision.
For example, if the axis_domination_confidence value is 1 and this
is multiplied by the unclipped motion component, the motion will be
locked onto and integrated quickly in gesture detection algorithms.
However, if no motion component has been locked onto, and motion is
being integrated but the dominant motion component is borderline,
when the motion component is multiplied by a low
axis_domination_confidence value, this can dampen the motion and
extend the integration period. This can delay the triggering of a
decision on which motion components to pass and which motion
components to clip and ultimately the identification of gestures.
During this delay time, the motions can become more unambiguous.
Once locked, it is not necessary to apply the
axis_domination_confidence value any more.
[0061] Embodiments of the invention described above can be
implemented, for example, using touch sensor panels of the types
described in U.S. application Ser. No. 11/650,049 entitled
"Double-Sided Touch Sensitive Panel and Flex Circuit Bonding."Sense
channels of the types described in U.S. application Ser. No.
11/649,998 entitled "Proximity and Multi-Touch Sensor Detection and
Demodulation" can be used, for example, to detect touch and hover
events. The resulting image of touch can be further processed to
determine the location of the touch events, the identification of
finger contacts, and the identification of gestures as described,
for example, in U.S. application Ser. No. 11/428,522 entitled
"Identifying Contacts on a Touch Surface," U.S. application Ser.
No. 11/756,211 entitled "Multi-touch Input Discrimination," and
U.S. application Ser. No. 10/903,964 entitled "Gestures for Touch
Sensitive Input Devices." All of the preceding applications
referred to in this paragraph are incorporated by reference herein
in their entirety for all purposes.
[0062] FIG. 7 illustrates exemplary computing system 700 that can
include one or more of the embodiments of the invention described
above. Computing system 700 can include one or more panel
processors 702 and peripherals 704, and panel subsystem 706.
Peripherals 704 can include, but are not limited to, random access
memory (RAM) or other types of memory or storage, watchdog timers
and the like. Panel subsystem 706 can include, but is not limited
to, one or more sense channels 708, channel scan logic 710 and
driver logic 714. Channel scan logic 710 can access RAM 712,
autonomously read data from the sense channels and provide control
for the sense channels. In addition, channel scan logic 710 can
control driver logic 714 to generate stimulation signals 716 at
various frequencies and phases that can be selectively applied to
drive lines of touch sensor panel 724 at a voltage established by
charge pump 715. In some embodiments, panel subsystem 706, panel
processor 702 and peripherals 704 can be integrated into a single
application specific integrated circuit (ASIC).
[0063] Touch sensor panel 724 can include a capacitive sensing
medium having a plurality of drive lines and a plurality of sense
lines, although other sensing media can also be used. Each
intersection, adjacency or near-adjacency of drive and sense lines
can represent a capacitive sensing node and can be viewed as
picture element (pixel) 726, which can be particularly useful when
touch sensor panel 724 is viewed as capturing an "image" of touch.
(In other words, after panel subsystem 706 has determined whether a
touch event has been detected at each touch sensor in the touch
sensor panel, the pattern of touch sensors in the multi-touch panel
at which a touch event occurred can be viewed as an "image" of
touch (e.g. a pattern of fingers touching the panel).) Each sense
line of touch sensor panel 724 can drive sense channel 708 (also
referred to herein as an event detection and demodulation circuit)
in panel subsystem 706.
[0064] Computing system 700 can also include host processor 728 for
receiving outputs from panel processor 702 and performing actions
based on the outputs that can include, but are not limited to,
moving an object such as a cursor or pointer, scrolling or panning,
adjusting control settings, opening a file or document, viewing a
menu, making a selection, executing instructions, operating a
peripheral device coupled to the host device, answering a telephone
call, placing a telephone call, terminating a telephone call,
changing the volume or audio settings, storing information related
to telephone communications such as addresses, frequently dialed
numbers, received calls, missed calls, logging onto a computer or a
computer network, permitting authorized individuals access to
restricted areas of the computer or computer network, loading a
user profile associated with a user's preferred arrangement of the
computer desktop, permitting access to web content, launching a
particular program, encrypting or decoding a message, and/or the
like. Host processor 728 can also perform additional functions that
may not be related to panel processing, and can be coupled to
program storage 732 and display device 730 such as an LCD display
for providing a UI to a user of the device. Display device 730
together with touch sensor panel 724, when located partially or
entirely under the touch sensor panel, or partially or entirely
integrated with the touch sensor panel, can form touch screen
718.
[0065] Note that one or more of the functions described above can
be performed by firmware stored in memory (e.g. one of the
peripherals 704 in FIG. 7) and executed by panel processor 702, or
stored in program storage 732 and executed by host processor 728.
The firmware can also be stored and/or transported within any
computer-readable storage medium for use by or in connection with
an instruction execution system, apparatus, or device, such as a
computer-based system, processor-containing system, or other system
that can fetch the instructions from the instruction execution
system, apparatus, or device and execute the instructions. In the
context of this document, a "computer-readable storage medium" can
be any storage medium that can contain or store the program for use
by or in connection with the instruction execution system,
apparatus, or device. The computer readable storage medium can
include, but is not limited to, an electronic, magnetic, optical,
electromagnetic, infrared, or semiconductor system, apparatus or
device, a portable computer diskette (magnetic), a random access
memory (RAM) (magnetic), a read-only memory (ROM) (magnetic), an
erasable programmable read-only memory (EPROM) (magnetic), a
portable optical disc such a CD, CD-R, CD-RW, DVD, DVD-R, or
DVD-RW, or flash memory such as compact flash cards, secured
digital cards, USB memory devices, memory sticks, and the like.
[0066] The firmware can also be propagated within any transport
medium for use by or in connection with an instruction execution
system, apparatus, or device, such as a computer-based system,
processor-containing system, or other system that can fetch the
instructions from the instruction execution system, apparatus, or
device and execute the instructions. In the context of this
document, a "transport medium" can be any medium that can
communicate, propagate or transport the program for use by or in
connection with the instruction execution system, apparatus, or
device. The transport readable medium can include, but is not
limited to, an electronic, magnetic, optical, electromagnetic or
infrared wired or wireless propagation medium.
[0067] FIG. 8a illustrates exemplary mobile telephone 836 that can
include touch sensor panel 824 and computing system 842 for
implementing the image jaggedness filter, global baseline offset,
and motion component dominance factors described above according to
embodiments of the invention.
[0068] FIG. 8b illustrates exemplary digital media player 840 that
can include touch sensor panel 824 and computing system 642 for
implementing the image jaggedness filter, global baseline offset,
and motion component dominance factors described above according to
embodiments of the invention.
[0069] FIG. 8c illustrates exemplary personal computer 844 that can
include touch sensor panel (trackpad) 824 and computing system 842
for implementing the image jaggedness filter, global baseline
offset, and motion component dominance factors described above
according to embodiments of the invention. The mobile telephone,
media player, and personal computer of FIGS. 8a, 8b and 8c can
advantageously benefit from the image jaggedness filter, global
baseline offset, and motion component dominance factors described
above because implementation of these features can improve the
normalized outputs of the touch sensor panel and the recognition of
gestures.
[0070] Although embodiments of this invention have been fully
described with reference to the accompanying drawings, it is to be
noted that various changes and modifications will become apparent
to those skilled in the art. Such changes and modifications are to
be understood as being included within the scope of embodiments of
this invention as defined by the appended claims.
* * * * *