U.S. patent application number 16/538131 was filed with the patent office on 2019-11-28 for video stabilization.
The applicant listed for this patent is SKYPE. Invention is credited to Pontus Carlsson, Andrei Jefremov, David Yubeng Zhao.
Application Number | 20190364210 16/538131 |
Document ID | / |
Family ID | 44310605 |
Filed Date | 2019-11-28 |







United States Patent
Application |
20190364210 |
Kind Code |
A1 |
Jefremov; Andrei ; et
al. |
November 28, 2019 |
VIDEO STABILIZATION
Abstract
Method, device and computer program product for stabilizing a
video signal. In one embodiment, a plurality of frames of a video
signal are captured using a camera. A first motion of the camera is
determined, with the first motion exclusive of second motion
occurring while the shutter is open. Pixel displacement between
first and second frames of the video signal is determined based on
the determined first motion. An image of at least one of the first
and second frames is shifted in accordance with the pixel
displacement.
Inventors: |
Jefremov; Andrei; (Jarfalla,
SE) ; Zhao; David Yubeng; (Enebyberg, SE) ;
Carlsson; Pontus; (Bromma, SE) |
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Applicant: |
Name |
City |
State |
Country |
Type |
SKYPE |
Dublin |
|
IE |
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|
Family ID: |
44310605 |
Appl. No.: |
16/538131 |
Filed: |
August 12, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14242512 |
Apr 1, 2014 |
10412305 |
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16538131 |
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13296941 |
Nov 15, 2011 |
8711233 |
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14242512 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 5/23264 20130101;
H04N 5/3454 20130101; H04N 5/23267 20130101; H04N 5/23258
20130101 |
International
Class: |
H04N 5/232 20060101
H04N005/232 |
Foreign Application Data
Date |
Code |
Application Number |
May 31, 2011 |
GB |
1109071.9 |
Claims
1. A method of stabilizing a video signal, the method comprising:
capturing a plurality of frames of the video signal using a camera;
determining first motion of the camera, the determined first motion
exclusive of second motion occurring while the shutter is open;
determining a pixel displacement between first and second frames of
the video signal based on the determined first motion; and shifting
an image of at least one of the first and second frames in
accordance with the pixel displacement to thereby stabilize the
video signal.
2. The method of claim 1 further comprising: generating a plurality
of samples from a motion sensor representing the first motion; and
determining a displacement of the camera between the first frame of
the video signal and the second frame of the video signal based on
the plurality of samples, wherein the determining of the pixel
displacement is based on the determined displacement of the
camera.
3. The method of claim 2, further comprising determining rotational
motion of the camera based on the samples from the motion sensor,
and wherein the determining of the displacement of the camera
determines an angular displacement of the camera.
4. The method of claim 1, the operations further comprising:
determining a pixel displacement between the first frame and the
second frame; determining an accumulated pixel displacement based
on the pixel displacement between the first frame and the second
frame; determining a filtered accumulated pixel displacement based
on a weighted sum of the determined accumulated pixel displacement
and a filtered accumulated pixel displacement for the first frame,
and wherein the shifting of the image is in accordance with the
filtered accumulated pixel displacement.
5. The method of claim 1, wherein the image comprises a stride
value indicating memory space of the image, a plurality of pixel
values, a pointer indicating a position of a first pixel of the
image, and a width value indicating a width of the image, wherein
said shifting of the image comprises adjusting the pointer and the
width value without adjusting the stride value.
6. The method of claim 1 wherein the image comprises a plurality of
image planes which are each represented by a respective plurality
of pixel values, a respective pointer indicating the position of a
first pixel of the image plane, and a respective width value
indicating the width of the image plane, wherein the image planes
are shifted together by adjusting their respective pointers and
width values without adjusting the stride value.
7. The method of claim 1 further comprising rounding the determined
pixel displacement to an integer-pixel displacement.
8. A computer program product for stabilizing a video signal, the
computer program product being embodied on a computer-readable
medium comprising instructions that when executed by a hardware
processor of a device configure the hardware processor to perform
operations comprising: capturing a plurality of frames of the video
signal using a camera; determining first motion of the camera, the
determined first motion exclusive of second motion occurring while
a shutter of the camera is open; determining a pixel displacement
between first and second frames of the video signal based on the
determined first motion; and shifting an image of at least one of
the first and second frames in accordance with the pixel
displacement to thereby stabilize the video signal.
9. The computer program product of claim 8, the operations further
comprising: generating a plurality of samples from a motion sensor
representing the first motion; and determining a displacement of
the camera between the first frame of the video signal and the
second frame of the video signal based on the plurality of samples,
wherein the determining of the pixel displacement is based on the
determined displacement of the camera.
10. The computer program product of claim 9, the operations further
comprising determining rotational motion of the camera based on the
samples from the motion sensor, and wherein the determining of the
displacement of the camera determines an angular displacement of
the camera.
11. The computer program product of claim 8, the operations further
comprising determining a pixel displacement between the first frame
and the second frame; determining an accumulated pixel displacement
based on the pixel displacement between the first frame and the
second frame; determining a filtered accumulated pixel displacement
based on a weighted sum of the determined accumulated pixel
displacement and a filtered accumulated pixel displacement for the
first frame, and wherein the shifting of the image is in accordance
with the filtered accumulated pixel displacement.
12. The computer program product of claim 8, wherein the image
comprises a stride value indicating memory space of the image, a
plurality of pixel values, a pointer indicating a position of a
first pixel of the image, and a width value indicating a width of
the image, wherein said shifting of the image comprises adjusting
the pointer and the width value without adjusting the stride
value.
13. The computer program product of claim 8, wherein the image
comprises a plurality of image planes which are each represented by
a respective plurality of pixel values, a respective pointer
indicating the position of a first pixel of the image plane, and a
respective width value indicating the width of the image plane,
wherein the image planes are shifted together by adjusting their
respective pointers and width values without adjusting the stride
value.
14. The computer program product of claim 8, further comprising
rounding the determined pixel displacement to an integer-pixel
displacement.
15. A device configured to stabilize a video signal, the device
comprising: a camera configured to capture a plurality of frames of
the video signal; hardware processing circuitry configured to
perform operations comprising: capturing a plurality of frames of
the video signal using a camera; determining first motion of the
camera, the determined first motion exclusive of second motion
occurring while a shutter of the camera is open; determining a
pixel displacement between first and second frames of the video
signal based on the determined first motion; and shifting an image
of at least one of the first and second frames in accordance with
the pixel displacement to thereby stabilize the video signal.
16. The device of claim 15, further comprising a motion sensor, the
operations further comprising: generating a plurality of samples
from the motion sensor representing the first motion; and
determining a displacement of the camera between the first frame of
the video signal and the second frame of the video signal based on
the plurality of samples, wherein the determining of the pixel
displacement is based on the determined displacement of the
camera.
17. The device of claim 16, the operations further comprising
determining rotational motion of the camera based on the samples
from the motion sensor, and wherein the determining of the
displacement of the camera determines an angular displacement of
the camera.
18. The device of claim 15, the operation further comprising
determining a pixel displacement between the first frame and the
second frame; determining an accumulated pixel displacement based
on the pixel displacement between the first frame and the second
frame; determining a filtered accumulated pixel displacement based
on a weighted sum of the determined accumulated pixel displacement
and a filtered accumulated pixel displacement for the first frame,
and wherein the shifting of the image is in accordance with the
filtered accumulated pixel displacement.
19. The device of claim 15, wherein the image comprises a stride
value indicating memory space of the image, a plurality of pixel
values, a pointer indicating a position of a first pixel of the
image, and a width value indicating a width of the image, wherein
said shifting of the image comprises adjusting the pointer and the
width value without adjusting the stride value.
20. The device of claim 15, wherein the image comprises a plurality
of image planes which are each represented by a respective
plurality of pixel values, a respective pointer indicating the
position of a first pixel of the image plane, and a respective
width value indicating the width of the image plane, wherein the
image planes are shifted together by adjusting their respective
pointers and width values without adjusting the stride value.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of and claims priority to
U.S. patent application Ser. No. 14/242,512, filed Apr. 1, 2014,
and entitled "VIDEO STABILIZATION," which is a divisional of and
claims priority to U.S. patent application Ser. No. 13/296,941
filed Nov. 15, 2011 and U.S. patent application Ser. No. 13/296,941
claims priority under 35 U.S.C. .sctn. 119 or 365 to Great Britain
Application No. GB 1109071.9, filed May 31, 2011. The contents of
these prior applications are considered part of this application,
and are incorporated by reference in their entirety.
BACKGROUND
[0002] Cameras can be used to capture a sequence of images to be
used as frames of a video signal. Cameras may be fixed to stable
objects, for example a camera may be mounted on a stand such as a
tripod to thereby keep the camera still while the video frames are
captured. However, often cameras may be implemented in mobile
devices and are not necessarily mounted to fixed objects, for
example a camera may be held, or may be on a moving object such as
a vehicle. Movement of the camera while the camera is capturing
frames of a video signal may result in unwanted movement in the
video signal itself.
[0003] Image stabilization is a method that can be used to
compensate for the unwanted movement a video signal. Some systems
perform motion estimation in order generate motion vectors for use
by an image stabilization process. One such system is described in
"Online Video Stabilization Based on Particle Filters" by Junlan
Yang et. al. Image stabilization algorithms may consist of three
main parts: motion estimation, motion smoothing and motion
compensation. A motion estimation block may estimate local motion
vectors within the video signal and on the basis of these local
estimates calculate a global motion vector. A motion smoothing
block may then deal with filtering of the estimated global motion
vector in order to smooth the calculated value and prevent large
and undesirable differences between motion vectors calculated
previously. A motion compensation block may then shift an image in
the opposite direction to the filtered global motion vector to
thereby stabilize the video signal. The motion compensation block
may take into account sophisticated transformations like rotation,
warping or zooming.
[0004] It can require large amounts of processing resources to
perform image stabilization based on motion vectors as described
above. This can be a problem when the video signal is to be
stabilized in real time, i.e. when a stabilized version of the
video signal is to be used (e.g. transmitted in a video call or
output from a device) at the same time as it is being captured by
the camera. This can also be a problem when the device which is
performing the image stabilization is a small, mobile device such
as a mobile telephone in which the processing resources are
limited.
[0005] In recent years, motion sensors have become simpler and
cheaper to manufacture and the size of motion sensors has reduced
significantly. It is now feasible to implement motion sensors in
mobile devices. Motion sensors generate samples representing the
motion of the sensor. Two documents: "Using Sensors for Efficient
Video Coding in Hand-held devices" by Andy L. Lin and
"Accelerometer Based Digital Video Stabilization for General
Security Surveillance Systems" by Martin Drahansk et. al, mention
the possibility of using data from motion sensors for stabilization
of a video signal.
SUMMARY
[0006] The inventors have realised that the implementation of using
data from motion sensors for stabilization of a video signal can be
improved compared to the systems of the prior art. In particular,
the inventors have considered factors such as: handling
non-uniformly sampled sensor data; synchronization of sampled
sensor data with the timing of frames of the video signal taking
the shutter speed of the camera into account; fast pixel shifting
of an image of one of the frames of the video signal by pointer
modification; and how to select sensor sampling rate. These factors
have not been considered in the references cited in the background
section above.
[0007] According to a first aspect there is provided a method of
stabilizing a video signal, the method comprising: capturing a
plurality of frames of the video signal using a camera; using a
motion sensor associated with the camera to generate a plurality of
samples representing motion of the camera; using the samples to
determine a displacement of the camera between a first time and a
second time, wherein the first time corresponds to an exposure time
midpoint of a first frame of the video signal and the second time
corresponds to an exposure time midpoint of a second frame of the
video signal; and using the determined displacement to compensate
for motion in the video signal between the first and second frames
caused by the motion of the camera, to thereby stabilize the video
signal.
[0008] Time stamps provided by the camera for the frames of the
video signal may relate to the time at which a shutter of the
camera closes (i.e. the end time of the frame). However, the
inventors have identified that in order to effectively determine
the displacement (e.g. an angular displacement) between the first
and second frames of the video signal using data from the motion
sensor (e.g. a rotational motion sensor), it is advantageous to
determine the displacement of the camera between the midpoints of
the exposure times of the frames. Using the midpoints of the
exposure times of the frames provides a more accurate
representation of the displacement of the camera between the first
and second frames. When mapping camera displacement to pixel
displacement, this method provides better estimation of pixel
displacement than using the end times of the frames.
[0009] In various embodiments, the motion of the camera is
rotational motion, the motion sensor is a rotational motion sensor
and the displacement of the camera is an angular displacement of
the camera. The using of the samples to determine an angular
displacement of the camera between a first time and a second time
may comprises: determining an angular velocity of the camera using
the samples; and integrating the determined angular velocity over
time from the first time to the second time to thereby determine
the angular displacement of the camera between the first time and
the second time.
[0010] In one embodiment, the angular displacement of the camera
between the first time and the second time is given by the
equation:
.DELTA. .theta. = .intg. t 1 - 0.5 e 1 t 2 - 0.5 e 2 .omega. ( t )
dt ##EQU00001##
where .DELTA..theta. is the angular displacement of the camera,
t.sub.1 is end time of the first frame, t.sub.2 is end time of the
second frame, e.sub.1 is the exposure time of the first frame,
e.sub.2 is the exposure time of the second frame and .OMEGA.(t) is
the angular velocity of the camera determined using the
samples.
[0011] The integrating of the determined angular velocity may
comprise interpolating the angular velocity between the times at
which the samples are generated and the method may further comprise
delaying the video signal thereby allowing the angular velocity of
the camera at the second time to be determined by said
interpolating the angular velocity between the times at which the
samples are generated.
[0012] The method may further comprise extrapolating the angular
velocity determined using the samples to thereby determine the
angular velocity of the camera at the second time.
[0013] The sample rate of the samples generated using the motion
sensor may be higher than the frame rate of the video signal.
Furthermore, the camera and the motion sensor may be situated
within a mobile device.
[0014] The using of the determined displacement to compensate for
motion in the video signal between the first and second frames
caused by the motion of the camera may comprise: determining a
pixel displacement representing motion in the video signal between
the first and second frames caused by the determined displacement
of the camera; filtering the pixel displacement; and shifting the
image of at least one of the first and second frames in accordance
with the filtered pixel displacement to thereby stabilize the video
signal. The filtering of the pixel displacement may comprise:
determining an accumulated pixel displacement based on said
determined pixel displacement for the second frame; and determining
a filtered accumulated pixel displacement for the second frame
based on a weighted sum of the determined accumulated pixel
displacement for the second frame and a filtered accumulated pixel
displacement for the first frame.
[0015] The method may further comprise adding a time offset to at
least one of (i) the captured plurality of frames, and (ii) the
generated plurality of samples, such that the timing of the
captured plurality of frames matches the timing of the generated
plurality of samples.
[0016] According to a second aspect there is provided a device for
stabilizing a video signal, the device comprising: a camera
configured to capture a plurality of frames of the video signal; a
motion sensor, associated with the camera, configured to generate a
plurality of samples representing motion of the camera; a
displacement determining block configured to use the samples to
determine a displacement of the camera between a first time and a
second time, wherein the first time corresponds to an exposure time
midpoint of a first frame of the video signal and the second time
corresponds to an exposure time midpoint of a second frame of the
video signal; and a motion compensation block configured to use the
determined displacement to compensate for motion in the video
signal between the first and second frames caused by the motion of
the camera, to thereby stabilize the video signal.
[0017] The motion sensor may be a gyroscopic motion sensor. The
device may be a mobile device.
[0018] According to a third aspect there is provided a method of
stabilizing a video signal, the method comprising: capturing a
plurality of frames of the video signal using a camera; determining
a pixel displacement representing motion in the video signal
between first and second frames of the video signal caused by
motion of the camera; and shifting an image of at least one of the
first and second frames in accordance with the pixel displacement
to thereby stabilize the video signal, wherein the image comprises
a stride value indicating memory space of the image, a plurality of
pixel values, a pointer indicating the position of a first pixel of
the image, and a width value indicating the width of the image,
wherein said shifting of the image comprises adjusting the pointer
and the width value without adjusting the stride value.
[0019] In this way, the image may be shifted and resized by simply
changing the pointer and the width value whilst keeping the stride
value constant. In this way, no copying of data in memory is
necessary. In other words, instead. of copying a crop area into a
new memory area (which can be a complex process), an image
representation is used that allows for independent width and stride
values. In this way, a new image can be created by changing the
pointer and the width value while the stride is kept intact (which
is a simpler process than copying a crop area into a new memory
area).
[0020] The image may comprise a plurality of image planes which are
each represented by a respective plurality of pixel values, a
respective pointer indicating the position of a first pixel of the
image plane, and a respective width value indicating the width of
the image plane, wherein the image planes may be shifted together
by adjusting their respective pointers and width values without
adjusting the stride value.
[0021] The method may further comprise rounding the determined
pixel displacement to an integer-pixel displacement.
[0022] The method may further comprise: using a motion sensor
associated with the camera to generate a plurally of samples
representing motion of the camera; and using the samples to
determine a displacement of the camera between a first frame of the
video signal and a second frame of the video signal, wherein the
determined displacement is used to determine said pixel
displacement.
[0023] The method may further comprise filtering the pixel
displacement.
[0024] According to a fourth aspect there is provided a device for
stabilizing a video signal, the device comprising: a camera
configured to capture a plurality of frames of the video signal; a
pixel displacement determining block configured to determine a
pixel displacement representing motion in the video signal between
first and second frames of the video signal caused by notion of the
camera; and an image shifting block configured to shift an image of
at least one of the first and second frames in accordance with the
pixel displacement to thereby stabilize the video signal, wherein
the image comprises a stride value indicating memory space of the
image, a plurality of pixel values, a pointer indicating the
position of a first pixel of the image, and a width value
indicating the width of the image, wherein the image shifting block
is configured to shift the image by adjusting the pointer and the
width value without adjusting the stride value.
[0025] According to a fifth aspect there is provided a method of
stabilizing a video signal, the method comprising: capturing a
plurality of frames of the video signal using a camera; determining
a portion of motion of the camera occurring whilst a shutter of the
camera is closed and not whilst the shutter of the camera is open;
determining a pixel displacement representing motion in the video
signal between first and second frames of the video signal caused
by, and corresponding to, the portion of motion of the camera; and
shifting an image of at least one of the first and second frames in
accordance with the pixel displacement to thereby stabilize the
video signal.
[0026] In this way, image stabilization may be reduced when motion
blur is present in the video signal. For high levels of camera
motion, motion blur will. be present in the frames of the video
signal for devices without physical stabilization, such as optical
or mechanical stabilization. Motion blur is caused when the camera
moves whilst the shutter of the camera is open and capturing one
frame of the video signal. If image stabilization were applied for
frames containing motion blur, the resulting video signal will
contain motion blur but no motion which can be detrimental because
a user viewing the video signal may perceive this to look strange
and/or unnatural. The inventors have realised that it may be
beneficial to have no compensation for motion that is made during
the time interval when the camera shutter is open. If the exposure
time (i.e. the time for which the shutter is open) is very short,
then having no compensation for motion that occurs whilst the
shutter is open will not make a significant difference. However, if
the exposure time (i.e. the time for which the shutter is open) is
very long, then little stabilization will be applied to the video
signal. Furthermore, motion blur will be accompanied by the
corresponding motion in the video signal, which may be perceived as
more natural to a user viewing the video signal.
[0027] The method may further comprise: using a motion sensor
associated with the camera to generate a plurality of samples
representing the portion of motion of the camera; and using the
samples to determine a displacement of the camera between the first
frame of the video signal and the second frame of the video signal,
wherein the determined displacement is used to determine said pixel
displacement.
[0028] According to a sixth aspect there is provided a device for
stabilizing a video signal, the device comprising: a camera
configured to capture a plurality of frames of the video signal; a
motion determining block configured to determine a portion of
motion of the camera occurring whilst a shutter of the camera is
closed and not whilst the shutter of the camera is open; a pixel
displacement determining block configured to determine a pixel
displacement representing motion in the video signal between first
and second frames of the video signal caused by, and corresponding
to, the portion of motion of the camera; and an image shifting
block configured to shift an image of at least one of the first and
second frames in accordance with the pixel displacement to thereby
stabilize the video signal.
[0029] According to a seventh aspect there is provided a computer
program product for stabilizing a video signal, the computer
program product being embodied on a non-transient computer-readable
medium and configured so as when executed on a processor of a
device to perform the operations of any of the methods described
herein.
[0030] There are described herein methods for using motion sensor
data to remove camera shaking (and other motion of the camera) from
a video signal to thereby stabilize the video signal, for example
for use in a mobile device. The methods may comprise synchronising
sensor data with camera frames and, in particular, determining the
angular displacement at the midpoint of the exposure time. The
methods may comprise filtering image displacement values using an
exponential filter suitable for use with non-uniformly sampled
sample data from the motion sensor. The methods may comprise
modifying the position of a pointer for shifting and/or cropping an
image of a frame of the video signal based on determined motion of
the camera. The methods may comprise adapting image stabilization
for frames of the video signal containing motion blur
BRIEF DESCRIPTION OF THE DRAWINGS
[0031] For a better understanding of the described embodiments and
to show how the same may be put into effect, reference will now be
made, by way of example, to the following drawings in which:
[0032] FIG. 1 shows a device according to one embodiment;
[0033] FIG. 2 is a flow chart for a process of stabilizing a video
signal according to one embodiment.
[0034] FIG. 3 is an exemplary graphical representation of a shutter
position of a camera over time;
[0035] FIG. 4 is an exemplary graphical representation of an
angular velocity of a camera over time; and
[0036] FIG. 5 is a representation of an image before and after a
cropping process.
DETAILED DESCRIPTION
[0037] FIG. 1 shows a device 100 according to one embodiment. The
device 100 may for example be a mobile device such as a mobile
telephone or other hand-held device. The device 100 comprises a
camera 102, a motion sensor 104, a CPU 106 and a memory 108. The
camera 102 is configured to capture images. The captured images may
be used to form a video signal, whereby each image is used as a
frame of the video signal and the images are captured at the frame
rate of the video signal. The frame rate may be, for example, 25
frames per second although the camera may operate at a different
frame rate. The minimum frame rate to achieve the perception of a
moving image is about fifteen frames per second, but this may
depend upon the person viewing the video signal and upon the
content that is in the video signal (i.e. how much motion there is
in the subject matter of the video signal). The motion sensor 104
is configured to generate samples representing the motion of the
device 100. Since both the motion sensor 104 and the camera 102 are
in the device 100, they are associated with each other such that
the samples generated by the motion sensor 104 can be used to
represent the motion of the camera 102. The CPU 106 is configured
to perform computational processes on the device 100 as is known in
the art. The memory 108 is used to store data in the device 100 as
is known in the art. The blocks 102, 104, 106 and 108 can
communicate with each other by sending data via a bus of the device
100 (not shown in FIG. 1) as is known in the art,
[0038] With reference to FIG. 2 there is now described a process of
stabilizing a video signal using the device 100 according to one
embodiment. In step S202 the camera 102 captures images to be used
as frames of a video signal. For example, the camera 102 may have
an array of light sensors which record the level of light that is
incident on the sensors during the time allocated to a frame of the
video signal. A shutter of the camera 102 is used to separate the
frames in time, such that during each frame the shutter is open for
a period of time and. closed for another period of time. The
captured frames of video signal are provided to a pre-processor
(e.g. implemented in a processing block by the CPU 106). The
pre-processor operates to stabilize the images in the frames of the
video signal before the frames are encoded using a video encoding
technique as is known in the art.
[0039] In step S204, while the camera 102 is capturing frames of
the video signal, the motion sensor 104 generates samples
representing the motion of the device 100. For example, the motion
sensor 104 may be a rotational motion sensor such as a gyroscope.
The gyroscope 104 measures angular velocity of the device 100 and
outputs samples representing the angular velocity at particular
intervals. The intervals may, or may not, be regular intervals. In
at least some instances, on average the sample rate of the samples
output from the gyroscope 104 is higher than the frame rate of the
video signal. For example, the sample rate output from the
gyroscope 104 may be 60 samples per second, which reflects the
maximum usual shaking frequency of the device 100 and is currently
independent of frame rate. The samples generated by the gyroscope
104 are provided to the pre-processor.
[0040] In step S206 the angular displacement of the camera 102
between two frames (frame 1 and frame 2) of the video signal is
determined. This determination may be performed by a processing
block of the CPU 106. The inventors have identified that in order
to effectively determine the angular displacement between the two
frames using data from the gyroscope 104, it is useful to integrate
the angular velocity over the time interval between the midpoints
of the exposure times of the frames captured by the camera 102. The
inventors have also determined that this can be particularly
problematic as it may not be possible to synchronise the sampling
rate of the gyroscope 104 with the frame rate of the camera 102,
particularly when: [0041] the camera 102 is arranged to adjust the
exposure times in dependence on the available light (which many
cameras are [0042] the time stamps for the frames of the video
signal provided by the camera 102 relate to the times at which the
shutter closes (i.e. the end times of the frames, as opposed to the
midpoints of the exposure times of the frames); and [0043] the
gyroscope data is not available at the midpoint of the exposure
time of the frames.
[0044] As described above, the pre-processor receives video frames
from the camera 102 and also receives the samples from the
gyroscope 104. The samples from the gyroscope 104 are provided to
the pre-processor (e.g. at regular intervals), at a rate at least
equivalent to the frame rate of the video signal captured by the
camera 102. Using a higher sampling rate in the gyroscope 104 gives
more accurate angle estimates but can be more costly in terms of
CPU usage.
[0045] A time stamp, t.sub.1, provided by the camera 102 to a first
frame (frame 1) of the video signal indicates the end time of the
frame, i.e. the time at which the shutter of the camera 102 is
closed to end frame 1. Similarly, a time stamp, t.sub.2, provided
by the camera 102 to a second frame (frame 2) of the video signal
indicates the end time of the frame, i.e. the tune at which the
shutter of the camera 102 is closed to end frame 2. in order to
determine the angular displacement (.DELTA..theta.) of the device
100 between the first frame and the second frame, rather than using
the time stamps of the frames to denote the times of the frames, it
is more accurate to use the midpoints of the exposure time of frame
1 and frame 2. The exposure times of the first and second frames
are denoted by e.sub.1 and e.sub.2. The angular displacement is
determined by integrating the angular velocity (represented by the
samples output from the gyroscope 104) of the device 100 between a
time t.sub.1-0.5e.sub.1 and a time t.sub.2-0.5e.sub.2. Therefore
the angular displacement between frame 1 and frame 2 is given
by:
.DELTA..theta.=.theta.(t.sub.2)-.theta.(t.sub.1)=.intg..sub.t.sub.1.sub.-
-0.5e.sub.1.sup.t.sup.2.sup.-0.5e.sup.2.OMEGA.(t)dt
FIG. 3 is an exemplary graphical representation of a shutter
position of the camera 102 over time. The shutter of the camera 102
closes at time t.sub.1 at the end of frame 1. The shutter re-opens
again for the camera 102 to capture frame 2 and then closes at time
t.sub.2 at the end of frame 2. The exposure time of frame 1 is
shown as e.sub.1 and the exposure time of frame 2 is shown as
e.sub.2 in FIG. 3. The time over which the angular velocity is
integrated is denoted T.sub.12 in FIG. 3. It can be appreciated
from looking at FIG. 3 that integrating over the time T.sub.12
corresponds to integrating between the midpoint of the exposure
time of the first frame (at time t.sub.1-0.5e.sub.1) and the
midpoint of the exposure time of the second frame (at time
t.sub.2-0.5e.sub.2). FIG. 3 shows the open time of the shutter to
be equal to the closed time of the shutter, but this is just one
example. In some embodiments (implementing short exposure times)
the time for which the shutter is open is shorter than the time for
which the shutter is closed. In contrast, in other embodiments
(implementing long exposure times) the time for which the shutter
is open is longer than the time for which the shutter is
closed.
[0046] Since the samples of the gyroscope 104 are not synchronised
with the timings of the frames of the video signal captured by the
camera 102, it might be the case that the gyroscope 104 does not
generate samples at the midpoints of the frames (frame 1 and frame
2). In which case, the angular velocity of the device 100 at the
midpoints of the frames can be determined by interpolating the
angular velocity represented by the samples generated by the
gyroscope 104. The angular velocity is evaluated by interpolation
at any time instant, and the midpoints of the exposure times of the
frames define the integral interval used when calculating the
angular displacement according to the equation above.
[0047] FIG. 4 is an exemplary graphical representation of an
angular velocity of the camera 102 over time. The samples
representing the angular velocity of the device 100 generated by
the gyroscope 104 are shown in FIG. 4 as samples 402, 404, 406, 408
and 410. It can be seen that in the example shown in FIG. 4 the
timings of the samples of the gyroscope 104 are not regular. For
example, the time between the samples 404 and 406 is shorter than
the time between the samples 406 and 408. The dotted line
connecting the samples in FIG. 4 shows the value of the angular
velocity that can be determined as a function of time by
interpolating the angular velocity represented by the samples
generated by the gyroscope 104. The interpolated angular velocity
(shown by the dotted line) can be integrated between times
(t.sub.1-0.5e.sub.1) and (t.sub.2-0.5e.sub.2) in order to determine
the angular displacement of the camera 102 between the first and
second frames. FIG. 4 shows a simple linear interpolation between
the samples from the gyroscope 104. In other embodiment,more
advanced interpolation could be used.
[0048] There may arise a situation in which a frame to be
stabilized is received at the pre-processor after the latest sample
from the gyroscope 104. For example, when the frame 2 is captured
at the camera 102 the frame 2 may be received at the pre-processor
before any samples from the gyroscope have been generated
subsequent to the midpoint of the exposure time of the frame 2
(t.sub.2-0.5e.sub.2). For example frame 2 may be received at the
pre-processor before the sample 410 shown in FIG. 4. In this
situation, delay may be introduced into the video stream, in order
for the sample 410 to be received at the pre-processor before the
frame 2 is processed, thereby allowing the angular velocity at time
(t.sub.2-0.5e.sub.2) to be determined before the frame 2 is
processed by the pre-processor. Alternatively, the angular velocity
may be extrapolated from the previously received samples from the
gyroscope 104 in order to determine the angular velocity of the
device 100 at the time (t.sub.2-0.5e.sub.2).
[0049] In the case of no motion of the camera 102 (e.g. for fixed
placement of the device 100), the gyroscope 104 may be disabled in
order to save battery life. The state of no motion can be
determined by feedback from a video encoder which encodes the video
signal subsequent to the image stabilization method described
herein and implemented by the pre-processor. The video encoder may
perform motion estimation as part of the encoding process and as
such can determine whether the camera is g. A state of motion can
also be determined and used to enable the gyroscope 104 when the
camera 102 is moved. When the device 100 operates in the state of
no motion, the motion sensor 104 may be polled at a slow interval
to determine whether the device 100 has started moving again. There
may be computationally cheaper ways to determine when the device
100 starts moving, depending on hardware and Application
Programming Interfaces (APIs) implemented in the operating system
of the device 100.
[0050] The timings of the operation of the hardware used for the
camera 102 and for the gyroscope 104 might not match. This may be
because the camera 102 and the gyroscope 104 are implemented in
independent hardware chips. Therefore it may be beneficial to add
an offset to the time stamps of either (or both) the samples
generated by the gyroscope 104 and the frames of the video signals.
In this way the timing of the samples from the gyroscope 104 can be
matched with the timing of the frames of the video signal
correctly. The offset may be constant for a particular combination
of hardware chips. Therefore a. delay may be computed offline and
used at the device 100 without incurring a processing penalty for
the method described herein.
[0051] In step S208 a pixel displacement representing the motion of
the camera 102 is determined. In general, a rotation of the camera
102 results in an approximately constant pixel displacement across
the image of a frame of the video signal, independent of distances
to objects in the image. This is in contrast to linear camera
motion, for which pixel displacement is a function of the distance
to the object. A function (or algorithm) mapping the rotation of
the device 100 to a pixel displacement depends on parameters of the
camera 102 (e.g. focal length and width of lens of the camera 102)
and the resolution of the images captured by the camera 102.
Encoder feedback can be useful to determine the accuracy of the
samples generated by the gyroscope 104 and to adapt the mapping
algorithm. There are also some cases of motion and object placement
where the stabilization model described herein based on the samples
from the gyroscope 104 is not accurate (e.g. for rotation of the
camera 102 around a user's face, the user's face may be stable in
the middle of the frame but the gyroscope 104 detects rotation and
therefore the stabilization process will attempt to stabilize the
background) which may be detected by the encoder and fed back to
the stabilization algorithm. In this way the stabilization
algorithm can be adapted.
[0052] The pixel displacement determined in step S208 represents
the motion in the images of the frames of the video signal
resulting from the motion of the camera 102 (as opposed to motion
in the subject matter of the images). In this way, the pixel
displacement determined in step S208 represents unwanted motion in
the images of the frames of the video signal.
[0053] In step S210 the pixel displacement determined in step S208
is filtered. This is done in order to smooth the changes that are
applied to the video signal in the image stabilization process over
time to thereby provide a smoother stabilized video signal. The
filter used to filter the pixel displacement can be designed in
different ways, depending on, for example, the resolution of the
images captured by the camera 102, the acceptable delay which may
be applied to the video signal, and the allowed amount of cropping
which can be applied to the images of the original video signal
received at the pre-processor from the camera 102. For example,
higher resolution video frames may benefit from a larger filter
attenuation of high frequency changes to the pixel displacement
applied in the image stabilization process. On the other hand, the
amount of cropping sets a hard limit to the maximum filter
attenuation.
[0054] An exponential filter may be used which filters the pixel
displacements according to the equation:
x_filt(n)=(1-w)*x_filt(n-1)+w*x(n),
[0055] where n represents the frame number of the video signal, x
represents the accumulated displacement (or "position"), according
to the pixel displacement determined in step S208, and x_filt
represents the filtered accumulated displacement which is
subsequently used to determine how to align the input image in
order to stabilize it as described in more detail below. In this
way the filter acts as an exponential filter. When motion stops,
x_filt-x will converge to zero which implies no shifting of the
image. The filter smoothes out changes to the determined pixel
displacement over time, by basing the filtered pixel displacements
on the corresponding filtered pixel displacement of the previous
frame as well as on the pixel displacement determined for the
current frame in step S208. The weighting applied to the filtered
pixel displacement of the previous frame is (1-w) whereas the
weighting applied to the pixel displacement determined for the
current frame is w. Therefore adjusting the weighting parameter, w,
will adjust how responsive the filter is to changes in the pixel
displacement (x). A recursive (Infinite Impulse Response (IIR))
filter is more suited than a Finite Impulse Response (FIR) filter
when the output x_filt is clipped to be in the range [x-crop,
x+crop] as the clipped value is fed back to the filter loop and
makes subsequent output of x_filt less prone to clipping.
[0056] The weighting parameter, w, is adapted to the resolution and
instant frame rate of the video signal to obtain a constant
physical cut-off frequency, which is measured in Hertz. If the
filter were an ideal filter then the physical cut-off frequency
would define the highest frequency component of changes to x which
will be incorporated into x_filt. Changes to x which have higher
frequency than the cut-off frequency will be attenuated by an ideal
filter and will not be present in x_filt. However, the filter is
not an ideal filter and as such the cut-off frequency defines the
highest frequency for which the attenuation applied by the filter
is below 3 dB. So for non-ideal filters there will be some
attenuation below the cut-off frequency and there will not be
perfect attenuation above the cut-off frequency. The filter output
is clipped so that the difference between x_filt and x is not
larger than the frame cropping size. w is adapted so that the
physical cut-off frequency is constant, e.g. 0.5 Hz. From the
filter transfer function, a function w(fc, fs) can be derived that
maps a physical cut-off frequency fc to w. When the sampling
frequency (frame rate) fs changes, w also changes even though fc is
constant. The filter according to the filter equation above is well
suited for instant changing of the cut-off frequency (changing w),
compared to other filters.
[0057] In step S212 the image of the second frame (frame 2) is
shifted using the filtered pixel displacement from step S210. In
this way the motion in the image of the second frame (relative to
the first frame) due to the motion of the camera 102 is attenuated.
In other words, the filtered pixel displacement is used to
compensate for the motion in the video signal between the first and
second frames caused by the motion of the camera, to thereby
stabilize the video signal.
[0058] The filtered pixel displacements are rounded to full-pixel
displacements (i.e. integer-pixel displacements). This allows a
simple method to be employed to shift the image of the second
frame. The image is represented using a stride value indicating
memory space of the image, a plurality of pixel values, a pointer
indicating the position of a first pixel of the image, and a width
value indicating the width of the image. The shifting of the image
comprises adjusting the pointer and the width value without
adjusting the stride value. It can be seen that the width value is
independent of the stride value which allows the width of the image
to be changed without affecting the stride of the image. Therefore
the memory space of the image (e.g. in the memory 108) does not
need to be changed when the image is shifted (and/or resized). This
means that no copying of data in the memory 108 is necessary with
this approach. This is in contrast to a conventional method of
cropping an image in which the crop area of the image is copied
into a new memory area. Copying the crop area may be
computationally complex which may be detrimental, particularly when
the method is to be implemented on a mobile device in which the
processing resources available to the CPU 106 may be limited. With
the method described herein, since the width value is independent
of the stride value the new, shifted image can be created by
changing the pointer and the width while the stride is kept
intact.
[0059] The image may be represented by multiple image planes, for
example a luma plane (Y) and two chroma planes (U and V). The image
planes of the input image may be shifted and resized by simply
changing the pointers to the luma and chroma planes, thereby
modifying the width of the image planes whilst keeping the stride
intact. The image planes are shifted by the same amount to ensure
that the shifted image planes can be used together to represent the
shifted image.
[0060] In order for this image shifting process to be implemented,
the image planes require respective pointers, i.e. they cannot all
be represented by the same, single pointer. Furthermore, as
described above, it is necessary that the image has independent
width and stride values.
[0061] FIG. 5 is a representation of an image before and after a
shifting and cropping process. The original image is denoted 502
and the shifted and cropped image is denoted 504. It can be seen
that the stride value of the image is left unchanged, whereas the
width of the image is reduced. Furthermore, the original pointer
points to the top left pixel of the original image whereas the
adjusted pointer points to the top left pixel of the shifted and
cropped image (which is in a different position to the top left
pixel of the original image). In this way the image is shifted and
cropped simply be changing the width value and the pointer.
[0062] In summary of the method described above, e.g. with
reference to FIG. 2, the following stages are implemented in the
pre-processor to stabilize the images of the frames of the video
signal before the video signal is encoded with a video encoder:
[0063] 1. the angular displacement of the camera 102 between frame
1 and frame 2 is estimated (step S206),
[0064] 2. the estimated angular displacement is mapped to a pixel
displacement of the image of frame 2 (step S208);
[0065] 3. unintended motion in the image of frame 2 is removed by
applying a filter to the sequence of pixel displacements (or to the
accumulated pixel displacements as described above) (step S210);
and
[0066] 4. a stabilized image for frame 2 is created by shifting the
image to the position calculated by the filter (step S212). The
frame dimensions of the stabilized image for frame 2 are equal or
less than the corresponding dimensions of the original image for
frame 2. In other words, the stabilized images of the video signal
are constructed by cutting out a moving border within the original
images of the video signal captured by the camera 102.
[0067] In some embodiments, the image stabilization may be reduced
when motion blur is present in the video signal. When high levels
of motion are experienced by the camera 102, motion blur will be
present in the video. Therefore, if the image stabilization
described herein is applied to the frames of the video signal, then
the resulting video signal will contain motion blur but no motion,
which a user may perceive as looking unnatural or weird.
[0068] In one embodiment no compensation for motion of the camera
102 is made during the time interval when the camera shutter is
open (i.e. the exposure times of the frames of the video signal)
e.g. in the time interval [t.sub.1-e.sub.1, t.sub.1]. If the
exposure time is very short (i.e. the shutter is open for a much
shorter time than it is closed for) then this will not make a
significant difference. However, if the exposure time is very long
(i.e. the shutter is open for a much. longer time than it is closed
for), then little image stabilization will be applied to the video
signal. In this way it is ensured that motion blur will always have
the corresponding motion in the video signal, which is perceived as
looking more natural to a viewer of the video signal.
[0069] Determining the motion of the camera 102 from the samples
generated by the gyroscope 104 and determining the shutter speed is
particularly advantageous since this information can be used to
determine whether or not to apply the image stabilization, in view
of the motion blur that the video signal may experience, without
adding extra computational complexity.
[0070] It is also possible to address the issue of motion blur with
no corresponding motion using a pure software stabilizer, rather
than the image stabilizer described above which uses the samples
from the gyroscope 104 to determine the motion of the camera 102.
Software motion estimation typically finds the motion vectors
representing centres of shutter speed intervals. Analyzing motion
blur and finding what kind of motion produced this blur is more
complex with a software stabilizer implementation than when using
the samples from the gyroscope 104 to determine the motion of the
camera 102, in combination with shutter speed, as described
above.
[0071] In the embodiments described above, the motion sensor 104 is
a gyroscope which generates samples representing the rotational
motion of the device 100. In other embodiments, the motion sensor
104 may sense other types of motion, such as translational motion
and generate samples representing the translational motion of the
device 100. These samples can be used in the same way as described
above in relation to the rotational motion to stabilize the video
signal However, as described above, with translational motion the
pixel displacement will depend on the distance to the object in the
image and so this must be taken into account when determining the
pixel displacements. For example, multiple accelerometers may be
able to estimate rotational motion, and in this case accelerometers
can be used without further modification. For more general
translational stabilization, it may become more difficult to
implement the method described herein since different areas in the
image move by different amounts of pixels. However, if the distance
to the object is constant (and known it may be simple to implement
the method with translation motion. Even where the distance to the
objects is not constant (but is still known) it would be possible
to implement the method with translation motion but extra
complication is added in determining the pixel displacements caused
by the translation motion of the camera 102.
[0072] After stabilizing the video signal the video signal is
encoded using a video encoding process. The encoded video signal
may be transmitted, e.g. as part of a video call to another user or
as a broadcast signal. Therefore, it is important for the video
signal to be able to be stabilized and encoded in real-time (i.e.
with very little delay) for use in events such as video calls, or
other communication events where users are perceptually very aware
of delay in the signals. Alternatively, the encoded video signal
could be stored at the device 100, e.g. in the memory 108.
[0073] The method steps S206, S208, S210 and S212 could be
implemented at the device 100 in software or in hardware. For
example, the CPU 106 may execute processing blocks to implement the
steps S206, S208, S210 and S212. For example, a computer program
product for stabilizing a video signal may be provided, which can
be stored in the memory 108 and executed by the CPU 106. The
computer program product may be configured so as when executed on
the CPU 106 to perform the method steps S206, S208, S210 and S212.
Alternatively, hardware blocks may be implemented in the device 100
to implement the steps S206, S208, S210 and S212.
[0074] It should be understood that the block, flow, and network
diagrams may include more or fewer elements, be arranged
differently, or be represented differently. It should be understood
that implementation may dictate the block, flow, and network
diagrams and the number of block, flow, and network diagrams
illustrating the execution of embodiments.
[0075] It should be understood that elements of the block, flow,
and network diagrams described above may be implemented in
software, hardware, or firmware. In addition, the elements of the
block, flow, and network diagrams described above may be combined
or divided in any manner in software, hardware, or firmware. If
implemented in software, the software may be written in any
language that can support the embodiments disclosed herein. The
software may be stored on any form of non-transitory computer
readable medium, such as random access memory (RAM), read only
memory (ROM), compact disk read only memory(CD-ROM), flash memory,
hard drive, and so forth. In operation, a general purpose or
application specific processor loads and executes the software in a
manner well understood in the art.
[0076] Furthermore, while the described embodiments have been
particularly shown and described with reference to various
examples, it will be understood to those skilled in the art that
various changes in form and detail may be made without departing
from the spirit and scope of the claimed subject matter.
* * * * *