U.S. patent application number 15/648598 was filed with the patent office on 2017-10-26 for method and apparatus for processing three-dimensional (3d) pseudoscopic images.
The applicant listed for this patent is SuperD Co. Ltd.. Invention is credited to PEIYUN JIAN, YANQING LUO.
Application Number | 20170310942 15/648598 |
Document ID | / |
Family ID | 53218175 |
Filed Date | 2017-10-26 |
United States Patent
Application |
20170310942 |
Kind Code |
A1 |
LUO; YANQING ; et
al. |
October 26, 2017 |
METHOD AND APPARATUS FOR PROCESSING THREE-DIMENSIONAL (3D)
PSEUDOSCOPIC IMAGES
Abstract
A method for detecting three-dimensional (3D) pseudoscopic
images and a display device for detecting 3D pseudoscopic images
are provided. The method includes extracting corresponding feature
points in a first view and corresponding feature points in a second
view, wherein the first view and the second view form a current 3D
image; calculating an average coordinate value of the feature
points in the first view and an average coordinate value of the
feature points in the second view; based on the average coordinate
value of the feature points in the first view and the average
coordinate value of the feature points in the second view,
determining whether the current 3D image is pseudoscopic or not;
and processing the current 3D image when it is determined that the
current 3D image is pseudoscopic.
Inventors: |
LUO; YANQING; (Shenzhen,
CN) ; JIAN; PEIYUN; (Shenzhen, CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SuperD Co. Ltd. |
Shenzhen |
|
CN |
|
|
Family ID: |
53218175 |
Appl. No.: |
15/648598 |
Filed: |
July 13, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
15004514 |
Jan 22, 2016 |
9743063 |
|
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15648598 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06T 2207/10021
20130101; H04N 2013/0074 20130101; H04N 13/122 20180501; H04N
13/398 20180501; G06T 7/0002 20130101; H04N 13/106 20180501; G06T
2207/30168 20130101 |
International
Class: |
H04N 13/00 20060101
H04N013/00; G06T 7/00 20060101 G06T007/00 |
Foreign Application Data
Date |
Code |
Application Number |
Jan 22, 2015 |
CN |
201510033241.0 |
Claims
1-20. (canceled)
21. A method for detecting 3D pseudoscopic images, comprising:
extracting corresponding feature points in a first view and
corresponding feature points in a second view, wherein the first
view and the second view form a current 3D image; calculating an
average coordinate value of the feature points in the first view
and an average coordinate value of the feature points in the second
view; based on the average coordinate value of the feature points
in the first view and the average coordinate value of the feature
points in the second view, determining whether the current 3D image
is pseudoscopic or not, wherein when the first view is an upper
view and the second view is a lower view, determining that the
current 3D image is pseudoscopic when the average coordinate value
of the feature points in the first view is larger than or equal to
the average coordinate value of the feature points in the second
view, when the first view is a lower view and the second view is an
upper view, determining that the current 3D image is pseudoscopic
when the average coordinate value of the feature points in the
second view is larger than or equal to the average coordinate value
of the feature points in the first view; and processing the current
3D image when it is determined that the current 3D image is
pseudoscopic.
22. The method for detecting 3D pseudoscopic images according to
claim 21, wherein: the average coordinate value of the feature
points in the first view is an average of X-axis coordinate values
of the feature points in the first view; and the average coordinate
value of the feature points in the second view is an average of
X-axis coordinate values of the feature points in the second
view.
23. The method for detecting 3D pseudoscopic images according to
claim 21, wherein processing the current 3D image further includes:
adjusting the first view and the second view forming the current 3D
image when it is determined that the current 3D image is
pseudoscopic, such that pseudoscopy in the current 3D image is
corrected.
24. The method for detecting 3D pseudoscopic images according to
claim 23, wherein adjusting the first view and the second view when
the current 3D image is pseudoscopic further includes: changing a
relative order of the first view and the second view forming the
current 3D image.
25. The method for detecting 3D pseudoscopic images according to
claim 21, further including: selecting a plurality of 3D video
frames from a 3D video based on a predetermined rule, wherein each
3D video frame is a 3D image having a first view and a second view,
before extracting corresponding feature points in the first view
and corresponding feature points in the second view.
26. The method for detecting 3D pseudoscopic images according to
claim 25, further including: Recording detection results of
detecting 3D pseudoscopic images in each of the plurality of 3D
video frames; and Recording the number of times of detecting 3D
pseudoscopic images in the 3D video.
27. The method for detecting 3D pseudoscopic images according to
claim 26, further including: based on the number of times of
detecting 3D pseudoscopic images in the 3D video and the detection
results of detecting 3D pseudoscopic images in each of the
plurality of 3D video frames, determining whether the 3D video is
pseudoscopic or not.
28. The method for detecting 3D pseudoscopic images according to
claim 27, further including: when the 3D video is determined as
pseudoscopic, respectively changing a relative order of the first
view and the second view in each 3D video frame which is
pseudoscopic.
29. A display device for detecting 3D pseudoscopic images,
comprising one or more processors, memory, and one or more program
modules stored in the memory and to be executed by the one or more
processors, the one or more program modules comprising: a feature
extraction module configured to extract corresponding feature
points in a first view and corresponding feature points in a second
view, wherein the first view and the second view form a current 3D
image; an average value calculation module configured to calculate
an average coordinate value of the feature points in the first view
and an average coordinate value of the feature points in the second
view; and a decision module configured to determine whether the
current 3D image is pseudoscopic or not based on the average
coordinate value of the feature points in the first view and the
average coordinates values of the feature points in the second
view, wherein when the first view is an upper view and the second
view is a lower view, the decision module is configured to
determine that the current 3D image is pseudoscopic when the
average coordinate value of the feature points in the first view is
larger than or equal to the average coordinate value of the feature
points in the second view, when the first view is a lower view and
the second view is an upper view, the decision module is configured
to determine that the current 3D image is pseudoscopic when the
average coordinate value of the feature points in the second view
is larger than or equal to the average coordinate value of the
feature points in the first view.
30. The display device according to claim 29, wherein: the average
coordinate value of the feature points in the first view is an
average of X-axis coordinate values of the feature points in the
first view; and the average coordinate value of the feature points
in the second view is an average of X-axis coordinate values of the
feature points in the second view.
31. The display device according to claim 29, further including: a
pseudoscopic image processing module configured to adjust the first
view and the second view forming the current 3D image when the
decision module determines that the current 3D image is
pseudoscopic, such that pseudoscopy in the current 3D image is
corrected.
32. The display device according to claim 31, wherein pseudoscopic
image processing module is further configured to: change a relative
order of the first view and the second view forming the current 3D
image.
33. The display device according to claim 29, further including: a
selecting module configured to select a plurality of 3D video
frames from a 3D video based on a predetermined rule, wherein each
3D video frame is a 3D image having a first view and a second
view.
34. The display device according to claim 29, further including: a
recording module configured to record the number of times of
detecting 3D pseudoscopic images in the 3D video and detection
results of detecting 3D pseudoscopic images in each of the
plurality of 3D video frames.
35. The display device according to claim 34, wherein the decision
module is further configured to: based on the number of times of
detecting 3D pseudoscopic images in the 3D video and the detection
results of detecting 3D pseudoscopic images in each of the
plurality of 3D video frames, determine whether the 3D video is
pseudoscopic or not.
36. The display device according to claim 35, wherein the
pseudoscopic image processing module is further configured to: when
the decision module determines the 3D video is pseudoscopic,
respectively change a relative order of the first view and the
second view in each 3D video frame which is pseudoscopic.
Description
CROSS-REFERENCES TO RELATED APPLICATIONS
[0001] This application is a continuation application of U.S.
patent application Ser. No. 15/004,514, filed on Jan. 22, 2016,
which claims priority of Chinese Application No. 201510033241.0,
filed on Jan. 22, 2015, the entire contents of all of which are
hereby incorporated by reference.
FIELD OF THE INVENTION
[0002] The present disclosure generally relates to the field of
three-dimensional (3D) display technologies and, more particularly,
relates to a method for detecting 3D pseudoscopic images and a
display device thereof.
BACKGROUND
[0003] For a smartphone or a digital camera capable of capturing
three-dimensional (3D) images, it usually takes two images of a
same scene, in which the two images have a correct relative order
and a parallax between them, and then arranges the two images into
a 3D image. In addition, a user may upload two-dimensional (2D)
images and utilize a 3D image creating software to generate
corresponding 3D images of the uploaded 2D images. The user may
further generate a 3D video based on multiple 3D video frames (i.e.
3D images), which can be played back on a 3D video player.
[0004] However, the user may not notice the relative order between
the two images forming the 3D image or 3D video frame, for example,
a left eye view and a right eye view, and thus may arrange the two
images in an incorrect order, resulting an incorrect 3D image. For
example, the user's left eye may see the right eye view and the
user's right eye may see the left eye view, causing 3D image depth
to be reversed to the user. That is, a pseudoscopic image or a
pseudoscopic view may be generated and the viewing experience may
be affected.
[0005] According to the present disclosure, detection and
correction of the pseudoscopic image is of significant importance.
If the pseudoscopic image cannot be detected and corrected, the
user experience will be significantly degraded. To detect whether
there is a pseudoscopy between a left view and a right view may
often need to utilize corners respectively detected in the left
view and the right view.
[0006] The disclosed methods and systems are directed to solve one
or more problems set forth above and other problems.
BRIEF SUMMARY OF THE DISCLOSURE
[0007] One aspect of the present disclosure includes a method for
detecting three-dimensional (3D) pseudoscopic images. The method
includes extracting corresponding feature points in a first view
and corresponding feature points in a second view, wherein the
first view and the second view form a current 3D image; calculating
an average coordinate value of the feature points in the first view
and an average coordinate value of the feature points in the second
view; based on the average coordinate value of the feature points
in the first view and the average coordinate value of the feature
points in the second view, determining whether the current 3D image
is pseudoscopic or not; and processing the current 3D image when it
is determined that the current 3D image is pseudoscopic.
[0008] Another aspect of the present disclosure includes a display
device for detecting 3D pseudoscopic images. The display device
includes a feature extraction module configured to extract
corresponding feature points in a first view and corresponding
feature points in a second view, wherein the first view and the
second view form a current 3D image, an average value calculation
module configured to calculate an average coordinate value of the
feature points in the first view and an average coordinate value of
the feature points in the second view, and a decision module
configured to determine whether the current 3D image is
pseudoscopic or not based on the average coordinate value of the
feature points in the first view and the average coordinates values
of the feature points in the second view.
[0009] Other aspects of the present disclosure can be understood by
those skilled in the art in light of the description, the claims,
and the drawings of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The following drawings are merely examples for illustrative
purposes according to various disclosed embodiments and are not
intended to limit the scope of the present disclosure.
[0011] FIG. 1 illustrates a flow chart of an exemplary method for
detecting 3D pseudoscopic images consistent with disclosed
embodiments;
[0012] FIG. 2a and FIG. 2b illustrate exemplary feature points in
an exemplary method for detecting 3D pseudoscopic images consistent
with disclosed embodiments,
[0013] FIG. 3 illustrates a flow chart of another exemplary method
for detecting 3D pseudoscopic images consistent with disclosed
embodiments;
[0014] FIG. 4 illustrates a structural schematic diagram of an
exemplary display device consistent with disclosed embodiments;
[0015] FIG. 5 illustrates a block diagram of an exemplary display
device consistent with disclosed embodiments;
[0016] FIG. 6 illustrates a structural schematic diagram of another
exemplary display device consistent with disclosed embodiments;
and
[0017] FIG. 7 illustrates an exemplary display device consistent
with disclosed embodiments.
DETAILED DESCRIPTION
[0018] Reference will now be made in detail to exemplary
embodiments of the invention, which are illustrated in the
accompanying drawings. Hereinafter, embodiments consistent with the
disclosure will be described with reference to drawings. It is
apparent that the described embodiments are some but not all of the
embodiments of the present invention. Based on the disclosed
embodiments, persons of ordinary skill in the art may derive other
embodiments consistent with the present disclosure, all of which
are within the scope of the present invention.
[0019] 3D display device is usually based a parallax principle, in
which a left view for a left eye and a right view for a right eye
are separated by a lens or a grating and then received by the
user's left eye and right eye, respectively. The user's brain fuses
the left view and the right view to generate a correct visual
perception of 3D display, i.e., a 3D image with a correct depth
perception.
[0020] However, it is possible that the left eye receives the right
view while the right eye receives the left view, for example, two
images with an incorrect relative order are arranged into a 3D
image, or two images with an incorrect relative position are
synthesized into a 3D image, etc. In such cases, the user may
experience a pseudoscopic (reversed stereo/3D) image showing an
incorrect depth perception. For example, a box on a floor may
appear as a box shaped hole in the floor. Thus the viewing
experience may be greatly degraded.
[0021] The present disclosure provides a method for detecting 3D
pseudoscopic images, which may be implemented into a display
device. FIG. 7 illustrates an exemplary display device consistent
with disclosed embodiments. The display device 700 may be an
electronic device which is capable of capturing 3D images, such as
a smartphone, a tablet, and a digital camera, etc., or an
electronic device which is capable of playing and/or generating 3D
images such as a notebook, a TV, and a smartwatch, etc. Although
the display device 700 is shown as a smartphone, any device with
computing power may be used.
[0022] FIG. 5 illustrates a block diagram of an exemplary display
device consistent with disclosed embodiments. As shown in FIG. 5,
the display device 500 may include a processor 502, a display 504,
a camera 506, a system memory 508, a system bus 510, an
input/output module 512, and a mass storage device 514. Other
components may be added and certain devices may be removed without
departing from the principles of the disclosed embodiments.
[0023] The processor 502 may include any appropriate type of
central processing module (CPU), graphic processing module (GPU),
general purpose microprocessor, digital signal processor (DSP) or
microcontroller, and application specific integrated circuit
(ASIC). The processor 502 may execute sequences of computer program
instructions to perform various processes associated with the
display device.
[0024] The display 504 may be any appropriate type of display, such
as plasma display panel (PDP) display, field emission display
(FED), cathode ray tube (CRT) display, liquid crystal display
(LCD), organic light emitting diode (OLED) display, light emitting
diode (LED) display, or other types of displays.
[0025] The camera 506 may be an internal camera in the display
device 500 or may be an external camera connected to the display
device 500 over a network. The camera 506 may provide images and
videos to the display device.
[0026] The system memory 508 is just a general term that may
include read-only memory (ROM), random access memory (RAM) and etc.
The ROM may store necessary software for a system, such as system
software. The RAM may store real-time data, such as images for
displaying.
[0027] The system bus 510 may provide communication connections,
such that the display device may be accessed remotely and/or
communicate with other systems via various communication protocols,
such as transmission control protocol/internet protocol (TCP/IP),
hypertext transfer protocol (HTTP), etc.
[0028] The input/output module 512 may be provided for users to
input information into the display device or for the users to
receive information from the display device. For example, the
input/output module 512 may include any appropriate input device,
such as a remote control, a keyboard, a mouse, an electronic
tablet, voice communication devices, or any other optical or
wireless input devices.
[0029] Further, the mass storage device 514 may include any
appropriate type of mass storage medium, such as a CD-ROM, a hard
disk, an optical storage, a DVD drive, or other type of storage
devices.
[0030] During an operating process, the processor 502, executing
various software modules, may perform certain processes to display
images or videos to one or more users.
[0031] FIG. 1 illustrates a flow chart of an exemplary method for
detecting 3D pseudoscopic images consistent with disclosed
embodiments. As shown in FIG. 1, at the beginning, corresponding
feature points in a first view and corresponding feature points in
a second view are extracted respectively, in which the first view
and the second view may form a current 3D image (S101).
[0032] In particular, the feature points in the first view and the
feature points in the second view may also be called as interest
points, significant points, key points, etc., which may exhibit a
certain pattern in a local image, such as intersections of
different objects, intersections of different regions with
different colors, and points of discontinuity on a boundary of an
object, etc.
[0033] A display device may extract feature points in the first
view and the feature points in the second view based on Harris
corner detection algorithm or SUSAN corner detection algorithm,
etc. For example, the display device may extract feature parameters
of the feature points in the first view and feature parameters of
the feature points in the second view, the feature parameters may
include a Speeded Lip Robust Features (SURF), a Scale-invariant
feature transform (SIFT) feature, a Binary Robust Invariant
Scalable Keypoints (BRISK) feature, and a Binary Robust Independent
Elementary Features (BRIEF), etc.
[0034] Based on the feature parameters of the first view and the
feature parameters of the second view, the display device may match
the feature points in the first view and the feature points in the
second view, and then determine the corresponding feature points in
the first view and feature points in the second view.
[0035] For example, the feature parameters of the first view and
the feature parameters of the second view may be matched based on a
K approaching algorithm. After being determined, the corresponding
feature points in the first view and feature points in the second
view may be defined. For example, the feature points may be
disposed in an X-Y coordinate system, and given an X-axis
coordinate value and a Y-axis coordinate value.
[0036] After extracting the corresponding feature points in the
first view and the corresponding feature points in the second view,
an average coordinate value of the feature points in the first view
and an average coordinate value of the feature points in the second
view are calculated, respectively (S102).
[0037] The average coordinate value may be an average of X-axis
coordinate values of all the feature points in each view (i.e. the
first view or the second view), or an average of Y-axis coordinate
values of all the feature points in each view (i.e. the first view
or the second view).
[0038] For example, in one embodiment, a left view and a right view
may be adopted to form a current 3D image, the left view may be a
first view and the right view may be a second view. An average
coordinate value in the first view may be the sum of X-axis
coordinate values of all feature points in the first view divided
by the number of all the feature points in the first view. An
average coordinate value in the second view may be the sum of
X-axis coordinate values of all feature points in the second view
divided by the number of all the feature points in the second
view.
[0039] In one embodiment, an upper view and a lower view may be
adopted to form a current 3D image, the upper view may be a first
view and the lower view may be a second view. An average coordinate
value in the first view may be the sum of Y-axis coordinate values
of all feature points in the first view divided by the number of
all the feature points in the first view. An average coordinate
value in the second view may be the sum of Y-axis coordinate values
of all feature points in the second view divided by the number of
all the feature points in the second view.
[0040] Based on the average coordinate value of the feature points
in the first view and the average coordinates value of the feature
points in the second view, whether the current 3D image is
pseudoscopic or not may be determined (S103).
[0041] In particular, in one embodiment, a left view and a right
view may be used to form a current 3D image, and the left view may
be a first view and the right view may be a second view. If an
average coordinate value of feature points in the first view is
larger than or equal to an average coordinate value of the feature
points in the second view, the current 3D image may be determined
to be pseudoscopic. On the contrary, if the average coordinate
value of the feature points in the first view is smaller than the
average coordinate value of the feature points in the second view,
the current 3D image may be not pseudoscopic.
[0042] In another embodiment, a left view and a right view may be
used to form a current 3D image, and the right view may be a first
view and the left view may be a second view. If an average
coordinate value of feature points in the second view is larger
than or equal to an average coordinate value of feature points in
the first view, the current 3D image may be determined to be
pseudoscopic. On the contrary, if the average coordinate value of
the feature points in the second view is smaller than the average
coordinate value of the feature points in the first view, the
current 3D image may not be pseudoscopic.
[0043] Further, if the current 3D image is determined to be
pseudoscopic, the display device may be able to correct the
pseudoscopic image through processing the first view and the
second.
[0044] For example, in one embodiment, a left view and a right view
may be used to form a current 3D image, and the left view may be a
first view and the right view may be a second view. When the
current 3D image is determined to be pseudoscopic, the display
device may correct the pseudoscopic image through adjusting the
relative order or the relative position of the first view and the
second view. That is, the first view may become the right view
while the second view may become the left view.
[0045] In another embodiment, a left view and a right view may be
used to form the current 3D image, and the right view may be a
first view and the left view may be a second view. When the current
3D image is determined to be pseudoscopic, the display device may
correct the pseudoscopic image through adjusting the relative order
or the relative position of the first view and the second view.
That is, the first view may become the left view while the second
view may become the right view.
[0046] In another embodiment, an upper view and a lower view may be
adopted to form the current 3D image, the upper view may be a first
view and the lower view may be a second view. The current 3D image
is determined to be pseudoscopic. The display device may correct
the current pseudoscopic image through adjusting the relative order
or the relative position of the first view and the second view.
That is, the first view may become the lower view while the second
view may become the upper view.
[0047] In another embodiment, an upper view and a lower view may be
adopted to form the current 3D image, the lower view may be a first
view and the upper view may be a second view. The current 3D image
is determined to be pseudoscopic. The display device may correct
the current pseudoscopic image through adjusting the relative order
or the relative position of the first view and the second view.
That is, the first view may become the upper view while the second
view may become the lower view.
[0048] FIG. 2a and FIG. 2b illustrate exemplary feature points in
an exemplary method for detecting 3D pseudoscopic views consistent
with disclosed embodiments. As shown in FIG. 2a, corners (i.e.
features points) are detected in a first view. Six corners may be
detected and coordinate values of the six corners in an X-Y
coordinate system are L1 (1,2), L2 (1,4), L3 (2,5), L4 (3,4), L5
(3,2), L6 (2,1), respectively.
[0049] As shown in FIG. 2b, six corners may be detected in a second
view and coordinate values of the six corners in the X-Y coordinate
system are R1 (2,3), R2 (2,5), R3 (3,6), R4 (4,5), R5 (4,3), R6
(3,2), respectively. The six corners (i.e. feature points) in the
first view may correspond to the six corners (i.e. feature points)
in the second view. The first view and the second view may be
adopted to form a current 3D image.
[0050] An average coordinate value in the first view may be the sum
of X-axis coordinate values of all the feature points in the first
view divided by the number of all the feature points in the first
view. That is, A=(2+4+5+4+2+1)/6=3. An average coordinate value in
the second view may be the sum of X-axis coordinate values of all
the feature points in the second view divided by the number of all
the feature points in the second view. That is,
B=(3+5+6+5+3+2)/6=4.
[0051] Because the average coordinate value of the feature points
in the first view is smaller than the average coordinate value of
the corresponding feature points in the second view, the current 3D
image may be not pseudoscopic, and a correction may not be
required.
[0052] If the current 3D image is pseudoscopic, the pseudoscopic
image may need to be corrected. In particular, the pseudoscopic
image may be corrected through adjusting the relative order or
relative position of the first view and the second view when
generating the current 3D image or displaying the current 3D image.
For example, if FIG. 2b shows a first view and FIG. 2a shows a
second view, the relative order of the first view and the second
view may be exchanged to correct the pseudoscopic image.
[0053] Further, a user may utilize a 3D video player implemented in
a display device to play a 3D video. However, before playing the 3D
video, detecting 3D pseudoscopic images (i.e. the pseudoscopic
image detection) in the 3D video may be highly desired, in case the
3D video may include any pseudoscopic video frames (i.e.,
pseudoscopic images) which may affect the viewing experience. The
display device may correct the pseudoscopic video frames as
described above, and then play the corrected 3D video. Thus, 3D
video frames may have to be selected before extracting the
corresponding feature points in the first view and the
corresponding feature points in the second view.
[0054] FIG. 3 illustrates a flow chart of another exemplary method
for detecting 3D pseudoscopic images consistent with disclosed
embodiments. As shown in FIG. 3, at the beginning, a plurality of
3D video frames (i.e. a 3D image) in a 3D video are selected based
on a predetermined rule (S300). Each 3D image may include a first
view and a second view. As used in the present disclosure, two
views are used to form the 3D image. However, any appropriate
number of views may be used.
[0055] In particular, the predetermined rule, i.e., the selection
of the 3D video frames, may be random but not repeated or may be
based on a certain interval, which is only for illustrative
purposes and is not intended to limit the scope of the present
invention. Further, for one 3D video, a maximum number of detecting
3D pseudoscopic images (indicating maximum times of detecting 3D
pseudoscopic images) and a minimum number of detecting 3D
pseudoscopic images (indicating minimum times of detecting
pseudoscopic) may be determined. For example, the maximum number of
detecting 3D pseudoscopic images may be Q, and the minimum number
of detecting 3D pseudoscopic images may be P. Q and P are positive
integers, respectively.
[0056] After the plurality of 3D video frames (i.e. 3D images) are
selected, each 3D video frame (i.e. 3D image) may be detected for
pseudoscopic images. For a current 3D video frame (i.e. 3D image)
having a first view and a second view, as shown in FIG. 3, at the
beginning, corresponding feature points in the first view and
corresponding feature points in the second view forming the current
3D image are extracted, respectively (S301). Then an average
coordinate value of the feature points in the first view and an
average coordinate value of the feature points in the second view
are calculated respectively (S302). Based on the average coordinate
value of the feature points in the first view and the average
coordinates value of the feature points in the second view, whether
the current 3D image is pseudoscopic or not may be determined
(S303). The Steps of S301, S302 and S303 may be similar to those of
S101, S102 and S103 in FIG. 1, details of which are not repeated
here while certain differences are explained.
[0057] The display device may further record S number of detecting
3D pseudoscopic images in the 3D video and corresponding detection
results of the multiple 3D video frames (i.e. 3D images). Then,
based on the number S and the corresponding detection results of
the multiple 3D video frames (i.e., 3D images), the display device
may determine whether the 3D video is pseudoscopic or not.
[0058] For example, S number of pseudoscopic image detections may
be performed in the 3D video, among which N number of 3D video
frames (i.e. 3D images) may be determined to be pseudoscopic, M
number of 3D video frames (i.e. 3D images) may be determined to be
not pseudoscopic and T number of pseudoscopic image detections may
be failed. In particular, S=M+N+T, S, M, N and T are positive
integers respectively. P denotes the minimum number of detecting 3D
pseudoscopic images in the 3D video, P is a positive integer.
[0059] If the value of M/S is larger than a predetermined threshold
value, the 3D video may not be determined to be pseudoscopic. If
the value of N/S is larger than a predetermined threshold value,
the 3D video may be determined to be pseudoscopic. The
predetermined threshold value may be determined according to
requirements of 3D viewing experience. Various requirements may
have various threshold values.
[0060] For example, according to certain requirements of 3D viewing
experience, the predetermined threshold value may be set as
approximately 0.7. That is, if a condition of S>=P and
(M/S)>0.7 is satisfied, the 3D video may not be determined to be
pseudoscopic and the pseudoscopic image detection in the 3D video
may end. If the condition of S>=P and (M/S)>0.7 is not
satisfied, the pseudoscopic image detection in the 3D video may
have to continue.
[0061] If a condition of S>=P and (N/S)>0.7 is satisfied, the
3D video may be determined to be pseudoscopic and the pseudoscopic
image detection in the 3D video may end. If the condition of
S>=P and (N/S)>0.7 is not satisfied, the pseudoscopic image
detection in the 3D video may have to continue.
[0062] If S>Q, the pseudoscopic image detection in the 3D video
may be determined to be failed and the pseudoscopic image detection
in the 3D video may end, otherwise the pseudoscopic image detection
in the 3D video may have to continue. Q denotes the maximum number
of the detecting 3D pseudoscopic images in the 3D video, and P
denotes the minimum number of detecting 3D pseudoscopic images in
the 3D video. In particular, Q>P, a preferred value of P may be
5 and a preferred value of Q may be 10.
[0063] If the 3D video is determined to be pseudoscopic, the
pseudoscopic video frames (i.e., pseudoscopic image) in the 3D
video may need to be corrected through adjusting the relative order
or relative position of the first view and the second view in the
pseudoscopic video frames (i.e., pseudoscopic image),
respectively.
[0064] Through respectively calculating the average coordinate
value of the feature points in the first view and the average
coordinate value of the feature points in the second view, the
display device may be able to determine whether the current 3D
image is pseudoscopic or not. Further, based on the results of the
pseudoscopic image detection, the display device may determine
whether the relative order of the relative position of the first
view and the second view forming the current 3D image needs to be
changed. Thus, the display device may enable the user to watch 3D
images/3D videos with correct depth perceptions, and enhance the
viewing experience.
[0065] FIG. 4 illustrates a structural schematic diagram of an
exemplary display device consistent with disclosed embodiments. The
display device 400 may be an electronic device which is capable of
capturing 3D images, such as a smartphone, a tablet, and a digital
camera, etc., or an electronic device which is capable of playing
and/or generating 3D images such as a notebook, a TV, and a
smartwatch, etc. (e.g., FIG. 7)
[0066] As shown in FIG. 4, the display device 400 may include a
feature extraction module 401, an average value calculation module
402 and a decision module 403. All of the modules may be
implemented in hardware, software, or a combination of hardware and
software. Software programs may be stored in the system memory 508,
which may be called and executed by the processor 502 to complete
corresponding functions/steps.
[0067] The feature extraction module 401 may be configured to
extract corresponding feature points in a first view and in a
second view, in which the first view and the second view may form a
current 3D image. The average value calculation module 402 may be
configured to calculate an average coordinate value of the feature
points in the first view and an average coordinate value of the
feature points in the second view. Based on the average coordinate
value of the feature points in the first view and the average
coordinates values of the feature points in the second view, the
decision module 403 may be configured to determine whether the
current 3D image is pseudoscopic or not.
[0068] For example, in one embodiment, a left view and a right view
may be adopted to form a current 3D image, a first view may be the
left view and a second view may be the right view. If an average
coordinate value of feature points in the first view is larger than
or equal to an average coordinate value of feature points in the
second view, the decision module 403 may determine the current 3D
image to be pseudoscopic.
[0069] In particular, the average coordinate value of the feature
points in the first view may be the sum of all X-axis coordinate
values of all the feature points in the first view divided by the
number of all the feature points in the first view. The average
coordinate value of the feature points in the second view may be
the sum of all X-axis coordinate values of all the feature points
in the second view divided by the number of all the feature points
in second first view.
[0070] In another embodiment, a left view and a right view may be
adopted to form a current 3D image, a first view may be the right
view and a second view may be the left view. If an average
coordinate value of feature points in the second view is larger
than or equal to an average coordinate value of feature points in
the first view, the decision module 403 may determine that the
current 3D image to be pseudoscopic.
[0071] In particular, the average coordinate value of the feature
points in the first view may be the sum of all X-axis coordinate
values of all the feature points in the first view divided by the
number of all the feature points in the first view. The average
coordinate value of the feature points in the second view may be
the sum of all X-axis coordinate values of all the feature points
in the second view divided by the number of all the feature points
in second first view.
[0072] FIG. 6 illustrates a structural schematic diagram of another
exemplary display device consistent with disclosed embodiments. As
shown in FIG. 6, the display device 600 may include a feature
extraction module 601, an average value calculation module 602 and
a decision module 603, which may perform similar functions as the
modules in FIG. 4. The similarities between FIG. 4 and FIG. 6 are
not repeated here, while certain differences are explained.
[0073] The display device 600 may further include a pseudoscopic
image processing module 604. If the current 3D image is
pseudoscopic, the pseudoscopic image processing module may be
configured to correct the pseudoscopic image through processing the
first view and the second view forming the current 3D image. In
particular, the pseudoscopic image processing module may adjust the
relative order or relative position of the first view and the
second view.
[0074] The display device 600 may also include a selecting module
605 configured to select 3D video frames (i.e., 3D images) in a 3D
video based on a predetermined rule. Each 3D video frame (i.e., 3D
image) may include a first view and a second view.
[0075] The display device 600 may also include a recording module
606 configured to record the number of detecting 3D pseudoscopic
images in the 3D video (i.e. times of detecting 3D pseudoscopic
images in the 3D video) and corresponding detection results of
detecting 3D pseudoscopic images in the 3D video. Based on the
number of detecting 3D pseudoscopic images in the 3D video and the
corresponding detection results of detecting 3D pseudoscopic images
in the 3D video, the decision module 603 may determine whether the
3D video is pseudoscopic or not. If the 3D video is determined to
be pseudoscopic, the pseudoscopic image processing module may
adjust the relative order or relative position of the first view
and the second view in the pseudoscopic video frames (i.e.
pseudoscopic image) in the 3D video, respectively.
[0076] The display device consistent with disclosed embodiments may
be an electronic device implemented with various software modules
of detecting 3D pseudoscopic images consistent with disclosed
embodiments, in which the details of detecting 3D pseudoscopic
images may be referred to the previous description of detecting 3D
pseudoscopic images. It should be noted that, names of the software
modules are only for illustrative purposes, which are not intended
to limit the scope of the present invention.
[0077] The method for detecting 3D pseudoscopic images may be used
in applications such as capturing 3D images and playing 3D videos.
For a smartphone or a digital camera capable of capturing 3D
images, it usually takes two images of a same scene, in which the
two images have a correct relative order and a parallax between
them, and then arranges the two images into a 3D image. In
addition, a user may upload 2D images and utilize a 3D image
creating software to generate corresponding 3D images of the
uploaded 2D images. The user may further generate a 3D video based
on multiple 3D video frames (i.e., 3D images), which can be played
back on a video player.
[0078] However, the user may not notice the relative order between
the two images forming the 3D image or 3D video frame, and thus may
arrange the two images in an incorrect order, resulting an
incorrect 3D image. That is, a pseudoscopic image or a pseudoscopic
view may be generated and the viewing experience may be
affected.
[0079] Through respectively calculating the average coordinate
value of the feature points in the first view and the average
coordinate value of the feature points in the second view, the
display device may be able to determine whether the current 3D
image is pseudoscopic or not. Further, based on the results of the
pseudoscopic image detection, the display device may determine
whether the relative order of the relative position of the first
view and the second view forming the current 3D image needs to be
changed. Thus, the display device may enable the user to watch 3D
images/3D videos with correct depth perceptions, and enhance the
viewing experience.
[0080] Those of skill would further appreciate that the various
illustrative modules and algorithm steps disclosed in the
embodiments may be implemented as electronic hardware, computer
software, or combinations of both. To clearly illustrate this
interchangeability of hardware and software, various illustrative
modules and steps have been described above generally in terms of
their functionality. Whether such functionality is implemented as
hardware or software depends upon the particular application and
design constraints imposed on the overall system. Skilled artisans
may implement the described functionality in varying ways for each
particular application, but such implementation decisions should
not be interpreted as causing a departure from the scope of the
present invention.
[0081] The steps of a method or algorithm disclosed in the
embodiments may be embodied directly in hardware, in a software
module executed by a processor, or in a combination of the two. A
software module may reside in RAM, flash memory, ROM, EPROM
(erasable programmable read-only memory), EEPROM (electrically
erasable programmable read-only memory), registers, hard disk, a
removable disk, a CD-ROM, or any other form of storage medium known
in the art.
[0082] The description of the disclosed embodiments is provided to
illustrate the present invention to those skilled in the art.
Various modifications to these embodiments will be readily apparent
to those skilled in the art, and the generic principles defined
herein may be applied to other embodiments without departing from
the spirit or scope of the invention. Thus, the present invention
is not intended to be limited to the embodiments shown herein but
is to be accorded the widest scope consistent with the principles
and novel features disclosed herein.
* * * * *