U.S. patent application number 16/160655 was filed with the patent office on 2019-02-14 for coding of 360 degree videos using region adaptive smoothing.
The applicant listed for this patent is Samsung Electronics Co., Ltd.. Invention is credited to Madhukar Budagavi, Andrew Dickerson, John Furton, Guoxin Jin, Ankur Saxena, Jeffrey Wilkinson.
Application Number | 20190052859 16/160655 |
Document ID | / |
Family ID | 55954681 |
Filed Date | 2019-02-14 |
View All Diagrams
United States Patent
Application |
20190052859 |
Kind Code |
A1 |
Budagavi; Madhukar ; et
al. |
February 14, 2019 |
CODING OF 360 DEGREE VIDEOS USING REGION ADAPTIVE SMOOTHING
Abstract
A video processing unit and method for region adaptive
smoothing. The image processing unit includes a memory and one or
more processors. The one or processors are operably connected to
the memory and configured to stitch together a plurality of video
frames into a plurality of equirectangular mapped frames of a
video. The one or processors are configured to define a top region
and a bottom region for each of the equirectangular mapped frames
of the video; perform a smoothing process on the top region and the
bottom region for each of the equirectangular mapped frames of the
video; and encode the smoothed equirectangular mapped frames of the
video.
Inventors: |
Budagavi; Madhukar; (Plano,
TX) ; Saxena; Ankur; (Dallas, TX) ; Wilkinson;
Jeffrey; (Flower Mound, TX) ; Furton; John;
(Dallas, TX) ; Dickerson; Andrew; (Allen, TX)
; Jin; Guoxin; (Evanston, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Samsung Electronics Co., Ltd. |
Suwon-si |
|
KR |
|
|
Family ID: |
55954681 |
Appl. No.: |
16/160655 |
Filed: |
October 15, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
14941436 |
Nov 13, 2015 |
10104361 |
|
|
16160655 |
|
|
|
|
62080104 |
Nov 14, 2014 |
|
|
|
62110053 |
Jan 30, 2015 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 19/167 20141101;
H04N 13/156 20180501; H04N 19/17 20141101; H04N 19/51 20141101;
H04N 13/243 20180501; H04N 19/46 20141101; H04N 19/117 20141101;
H04N 19/86 20141101; H04N 13/106 20180501; H04N 13/161
20180501 |
International
Class: |
H04N 13/161 20060101
H04N013/161; H04N 19/86 20060101 H04N019/86; H04N 19/167 20060101
H04N019/167; H04N 19/46 20060101 H04N019/46; H04N 19/17 20060101
H04N019/17; H04N 13/156 20060101 H04N013/156; H04N 13/106 20060101
H04N013/106; H04N 13/243 20060101 H04N013/243; H04N 19/51 20060101
H04N019/51; H04N 19/117 20060101 H04N019/117 |
Claims
1. A video processing unit comprising: a memory; and one or more
processors operably connected to the memory, the one or more
processors configured to: use an equidistant mapping to simulate a
warped plain in a fisheye lens; derive a warped motion estimation;
and use the warped motion estimation as an additional mode for
inter-prediction in a video codec.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a divisional of U.S. patent
application Ser. No. 14/941,436 filed Nov. 13, 2015, which claims
priority to U.S. Provisional Patent Application No. 62/110,053
filed Jan. 30, 2015, and U.S. Provisional Patent Application No.
62/080,104 filed Nov. 14, 2014, entitled "MOTION ESTIMATING AND
COMPENSATION FOR 360 DEGREE VIDEO." the disclosures of which are
hereby incorporated by reference in their entirety.
TECHNICAL FIELD
[0002] The present application relates generally to generating
video data and, more specifically, to a coding of 360 degrees
videos using region adaptive smoothing.
BACKGROUND
[0003] 360 degrees video is a new way of experiencing immersive
video using devices such as GearVR. 360 degrees video enables
immersive "real life," "being there" experience for consumers by
capturing the 360 degree view of the world. Users can change their
viewpoint and dynamically view any part of the captured scene they
desire. 360 degrees videos require higher bitrates than
conventional videos due to increased video resolution (4K and
beyond) needed to support the wider field of view. Bitrate increase
is a limiting factor in providing high quality 360 degrees
immersive video viewing experience to consumers.
[0004] Hence, the bitrate requirements are also higher
necessitating the need for efficient compression. 360 degrees video
has unique characteristics that can be exploited to improve
compression efficiency. Due to the warping present in the video,
the motion in the video is frequently non-translational.
SUMMARY
[0005] Embodiments of the present disclosure provide, coding of 360
degree videos using region adaptive smoothing and motion estimating
and compensation for 360 degree video.
[0006] In one embodiment, a video processing unit capable of region
adaptive smoothing is provided. The image processing unit includes
a memory and one or more processors. The one or more processors are
operably connected to the memory and configured to stitch together
a plurality of video frames into a plurality of equirectangular
mapped frames of a video. The one or more processors are configured
to define a top region and a bottom region for each of the
equirectangular mapped frames of the video; perform a smoothing
process on the top region and the bottom region for each of the
equirectangular mapped frames of the video; and encode the smoothed
equirectangular mapped frames of the video.
[0007] In another embodiment, a video processing unit capable of
region adaptive smoothing is provided. The image processing unit
includes a receiver and one or more processors. The receiver is
configured to receive metadata and a smoothed equirectangular
mapped frames of a video. The one or more processors configured to
decode the smoothed equirectangular mapped frames of the video
smoothed across smoothed regions along an outside border of the
smoothed equirectangular mapped frames of a video; perform an
enhancement technique on the smoothed region and render each of the
equirectangular mapped frames of the video into a spherical
shape.
[0008] In yet another embodiment, a method for region adaptive
smoothing is provided. The method includes stitching a plurality of
video frames into equirectangular mapped frames of a video,
respectively; defining a top region and a bottom region for each of
the equirectangular mapped frames of the video; performing a
smoothing process on the top region and the bottom region for each
of the equirectangular mapped frames of the video; and encoding the
smoothed equirectangular mapped frames of the video.
[0009] Before undertaking the DETAILED DESCRIPTION below, it may be
advantageous to set forth definitions of certain words and phrases
used throughout this patent document. The term "couple" and its
derivatives refer to any direct or indirect communication between
two or more elements, whether or not those elements are in physical
contact with one another. The terms "transmit," "receive," and
"communicate," as well as derivatives thereof, encompass both
direct and indirect communication. The terms "include" and
"comprise," as well as derivatives thereof, mean inclusion without
limitation. The term "or" is inclusive, meaning and/or. The phrase
"associated with," as well as derivatives thereof, means to
include, be included within, interconnect with, contain, be
contained within, connect to or with, couple to or with, be
communicable with, cooperate with, interleave, juxtapose, be
proximate to, be bound to or with, have, have a property of, have a
relationship to or with, or the like. The term "controller" means
any device, system or part thereof that controls at least one
operation. Such a controller may be implemented in hardware or a
combination of hardware and software and/or firmware. The
functionality associated with any particular controller may be
centralized or distributed, whether locally or remotely. The phrase
"at least one of," when used with a list of items, means that
different combinations of one or more of the listed items may be
used, and only one item in the list may be needed. For example, "at
least one of: A, B, and C" includes any of the following
combinations: A, B, C, A and B, A and C, B and C, and A and B and
C.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] For a more complete understanding of the present disclosure
and its advantages, reference is now made to the following
description taken in conjunction with the accompanying drawings, in
which like reference numerals represent like parts:
[0011] FIG. 1 illustrates an example computing system according to
various embodiments of the present disclosure;
[0012] FIGS. 2 and 3 illustrate example devices in a computing
system according to various embodiments of the present
disclosure;
[0013] FIG. 4 illustrates a 360 degrees video processing chain
according to various embodiments of the present disclosure;
[0014] FIGS. 5A, 5B, 5C, and 5D illustrate an example of stitching
and equirectangular mapping according to various embodiments of the
present disclosure;
[0015] FIG. 6 illustrates an equidistant mapping between a
rectangular plain and a warped plain according to various
embodiments of the present disclosure;
[0016] FIG. 7A illustrates the effects of warping after mapping
according to various embodiments of the present disclosure;
[0017] FIG. 7B illustrates the effects of warping before mapping
according to various embodiments of the present disclosure;
[0018] FIG. 8A illustrates a motion estimation according to various
embodiments of the present disclosure;
[0019] FIG. 8B illustrates a warped motion estimation according to
various embodiments of the present disclosure;
[0020] FIG. 9A illustrates an interpolation 900 of mapped pixels
915 by pixels 920 in frame f.sub.j according to various embodiments
of the present disclosure;
[0021] FIG. 9B illustrates interpolation techniques according to
various embodiments of the present disclosure;
[0022] FIG. 9C illustrates a motion vector predictor compensation
(MVPC) according to various embodiments of the present
disclosure;
[0023] FIG. 10 illustrates an additional warp mode in RDO search
according to various embodiments of the present disclosure;
[0024] FIG. 11 illustrates the 360 degrees video processing process
with such a region adaptive smoothing according to various
embodiments of the present disclosure;
[0025] FIG. 12A illustrates the normalized sphere with a radius of
one that is used to derive the heuristics for calculating the
variance of a Gaussian smoothing filter as a function of the image
row number y according to various embodiments of the present
disclosure;
[0026] FIG. 12B illustrates how .sigma..sup.2 varies with the
normalized image row number (normalized to be between negative one,
which is bottom of the image, to positive one, which is the top of
the image) for K equal to three according to various embodiments of
the present disclosure;
[0027] FIG. 13 illustrates a process for coding of 360 degrees
videos using region adaptive smoothing according to various
embodiments of the present disclosure;
[0028] FIG. 14 illustrates a process for coding of 360 degrees
videos using row position for a strength of the region adaptive
smoothing according to various embodiments of the present
disclosure;
[0029] FIG. 15 illustrates a 360 degrees video processing chain
according to various embodiments of the present disclosure;
[0030] FIGS. 16A and 16B illustrate alternative smoothing regions
according to various embodiments of the present disclosure; and
[0031] FIG. 17 illustrates squeezing the top region and bottom
region of an equirectangular mapped frame according to various
embodiments of the present disclosure.
DETAILED DESCRIPTION
[0032] FIGS. 1 through 17, discussed below, and the various
embodiments used to describe the principles of the present
disclosure in this patent document are by way of illustration only
and should not be construed in any way to limit the scope of the
disclosure. Those skilled in the art will understand that the
principles of the present disclosure may be implemented in any
suitably arranged system.
[0033] The following documents and standards descriptions are
hereby incorporated into the present disclosure as if fully set
forth herein:
[0034] [1] M. Narroschke and R. Swoboda, "Extending HEVC by an
affine motion model, pp. 321-324, IEEE Picture Coding Symposium,
2013.
[0035] [2] J. Zheng et. al., "Adaptive selection of motion models
for panoramic video," pp. 1319-1322, IEEE International Conference
on Multimedia and Expo, 2007.
[0036] Prior work that uses sophisticated motion models to code the
video, such as [1] and [2], can be used. However, a disadvantage of
these techniques is that they need modifications to video decoding
architecture and hence cannot be supported on existing devices.
[0037] 360 degrees video is created by warping and stitching images
from multiple cameras that cover the 360 degrees world. The
stitched image is then equirectangularly mapped into a
two-dimensional (2D) rectangular image that is then coded using
standard video codecs such as H.264/AVC and HEVC/H.265. During
playback the compressed video can be streamed or downloaded and
decoded. After decoding, the video is texture mapped onto a virtual
sphere in a 3D graphics environment with the viewer located at the
center of the virtual sphere. The viewer can navigate inside the
virtual sphere to see the view of the 360 degrees world he/she
desires and thereby experiencing an immersive experience. A
characteristic of the equirectangular mapping is that the top and
the bottom views occupy a larger number of pixels in the 2D
stitched image when compared to the actual area on the virtual
sphere. This disclosure exploits this characteristic of the
equirectangular mapping to provide bitrate savings. This disclosure
smooths the top and the bottom regions of video before encoding.
Since the pixels in the top and the bottom part of the stitched
picture have more resolution than what is perceptually noticeable,
the smoothing does not lead to perceptual quality degradation.
However, it results in bitrate saving since smooth regions require
less transform coefficients to be transmitted. The smoothing in
this disclosure can be fixed or varied depending on the regions of
the 2D image. The methods of this disclosure can achieve savings of
up to 20%. The smoothing is a pre-processing step at the encoding
side and not dependent on the type of the codec; hence it can be
easily supported using existing codecs.
[0038] This disclosure also deals with new types of video
sequences, i.e., 360 degree video sequences, for which multiple
views of a panoramic scene are warped and stitched. 360 degree
video sequences have many applications in virtual reality (VR)
devices. In order to transmit the 360 video sequences efficiently,
the multi-view sequences are not transmitted individually. Instead,
the warped and stitched version consisting of rectangular frames is
stored. The state-of-the-art video coding techniques, such as HEVC
and H.264/AVC, cannot fully utilize the characteristics of the
warped image space. Particularly, in regular video sequences,
motion estimation provides substantial compression gains in a video
codec. However, in the warped space, the object to be motion
estimated, e.g., a block of pixels will be deformed. Thus, the
motion estimation technique should be re-designed to comply with
the warped space.
[0039] In the High Efficiency Video Coding (HEVC) standard, there
are three modes in the Inter Prediction process. In the skip mode,
the transform coefficients are not transmitted and the coding unit
(CU) is represented as a prediction unit (PU) and the parameters
are obtained by merge mode. In the merge mode, the current PU
parameters are inferred from neighboring PU's. And normal inter
prediction mode, where the motion parameters are computed and
signaled.
[0040] In the Motion Vector Prediction, the spatial and temporal
neighboring PU motion vectors are used to predict current PU motion
vector.
[0041] FIG. 1 illustrates an example computing system 100 according
to this disclosure. The embodiment of the computing system 100
shown in FIG. 1 is for illustration only. Other embodiments of the
computing system 100 could be used without departing from the scope
of this disclosure.
[0042] As shown in FIG. 1, the system 100 includes a network 102,
which facilitates communication between various components in the
system 100. For example, the network 102 may communicate internet
protocol (IP) packets, frame relay frames, asynchronous transfer
mode (ATM) cells, or other information between network addresses.
The network 102 may include one or more local area networks (LANs),
metropolitan area networks (MANs), wide area networks (WANs), all
or a portion of a global network such as the Internet, or any other
communication system or systems at one or more locations.
[0043] The network 102 facilitates communications between at least
one server 104 and various client devices 106-114. Each server 104
includes any suitable computing or processing device that can
provide computing services for one or more client devices. Each
server 104 could, for example, include one or more processing
devices, one or more memories storing instructions and data, and
one or more network interfaces facilitating communication over the
network 102.
[0044] Each client device 106-114 represents any suitable computing
or processing device that interacts with at least one server or
other computing device(s) over the network 102. In this example,
the client devices 106-114 include a desktop computer 106, a mobile
telephone or smartphone 108, a personal digital assistant (PDA)
110, a laptop computer 112, and a tablet computer 114. However, any
other or additional client devices could be used in the computing
system 100.
[0045] In this example, some client devices 108-114 communicate
indirectly with the network 102. For example, the client devices
108-110 communicate via one or more base stations 116, such as
cellular base stations or eNodeBs. Also, the client devices 112-114
communicate via one or more wireless access points 118, such as
IEEE 802.11 wireless access points. Note that these are for
illustration only and that each client device could communicate
directly with the network 102 or indirectly with the network 102
via any suitable intermediate device(s) or network(s).
[0046] In this illustrative embodiment, computing system 100
provides coding of 360 degree videos using region adaptive
smoothing and motion estimating and compensation for 360 degree
video, as will be discussed in greater detail below. For example,
server 104 may provide for encoding of 360 degree videos using
region adaptive smoothing and motion estimating and compensation
for 360 degree video. Similarly, client devices 108-114 may receive
encoded images or videos from server 104 over network 102 and
decode the 360 degree videos using region adaptive smoothing and
motion estimating and compensation for 360 degree video.
[0047] Although FIG. 1 illustrates one example of a computing
system 100, various changes may be made to FIG. 1. For example, the
system 100 could include any number of each component in any
suitable arrangement. In general, computing and communication
systems come in a wide variety of configurations, and FIG. 1 does
not limit the scope of this disclosure to any particular
configuration. While FIG. 1 illustrates one operational environment
in which various features disclosed in this patent document can be
used, these features could be used in any other suitable
system.
[0048] FIGS. 2 and 3 illustrate example devices in a computing
system according to this disclosure. In particular, FIG. 2
illustrates an example server 200, and FIG. 3 illustrates an
example client device 300. The server 200 could represent the
server 104 in FIG. 1, and the client device 300 could represent one
or more of the client devices 106-114 in FIG. 1.
[0049] As shown in FIG. 2, the server 200 includes a bus system
205, which supports communication between one or more processors
210, at least one storage device 215, at least one communications
unit 220, and at least one input/output (I/O) unit 225.
[0050] The processor(s) 210 execute instructions that may be loaded
into a memory 230. The processor(s) 210 may include any suitable
number(s) and type(s) of processors or other devices in any
suitable arrangement. Example types of processor(s) 210 include
microprocessors, microcontrollers, digital signal processors, field
programmable gate arrays, application specific integrated circuits,
and discreet circuitry. The processor(s) 210 is configured to
perform operations for unlocking an electronic device with an
authenticated wearable device.
[0051] The memory 230 and a persistent storage 235 are examples of
storage devices 215, which represent any structure(s) capable of
storing and facilitating retrieval of information (such as data,
program code, and/or other suitable information on a temporary or
permanent basis). The memory 230 may represent a random access
memory or any other suitable volatile or non-volatile storage
device(s). The persistent storage 235 may contain one or more
components or devices supporting longer-term storage of data, such
as a ready only memory, hard drive, Flash memory, or optical
disc.
[0052] The communications unit 220 supports communications with
other systems or devices. For example, the communications unit 220
could include a network interface card or a wireless transceiver
facilitating communications over the network 102. The
communications unit 220 may support communications through any
suitable physical or wireless communication link(s).
[0053] The I/O unit 225 allows for input and output of data. For
example, the I/O unit 225 may provide a connection for user input
through a keyboard, mouse, keypad, touchscreen, or other suitable
input device. The I/O unit 225 may also send output to a display,
printer, or other suitable output device.
[0054] In this illustrative embodiment, server 200 may implement an
image processing unit that provides coding of 360 degree videos
using region adaptive smoothing and motion estimating and
compensation for 360 degree video, as will be discussed in greater
detail below. Note that while FIG. 2 is described as representing
the server 104 of FIG. 1, the same or similar structure could be
used in one or more of the client devices 106-114. For example, a
laptop or desktop computer could have the same or similar structure
as that shown in FIG. 2.
[0055] As shown in FIG. 3, the client device 300 includes an
antenna 305, a radio frequency (RF) transceiver 310, transmit (TX)
processing circuitry 315, a microphone 320, and receive (RX)
processing circuitry 325. The client device 300 also includes a
speaker 330, a one or more processors 340, an input/output (I/O)
interface (IF) 345, a touchscreen 350, a display 355, and a memory
360. The memory 360 includes a basic operating system (OS) program
361 and one or more applications 362.
[0056] The RF transceiver 310 receives, from the antenna 305, an
incoming RF signal transmitted by another component in a system.
The RF transceiver 310 down-converts the incoming RF signal to
generate an intermediate frequency (IF) or baseband signal. The IF
or baseband signal is sent to the RX processing circuitry 325,
which generates a processed baseband signal by filtering, decoding,
and/or digitizing the baseband or IF signal. The RX processing
circuitry 325 transmits the processed baseband signal to the
speaker 330 (such as for voice data) or to the processor(s) 340 for
further processing (such as for web browsing data).
[0057] The TX processing circuitry 315 receives analog or digital
voice data from the microphone 320 or other outgoing baseband data
(such as web data, e-mail, or interactive video game data) from the
processor(s) 340. The TX processing circuitry 315 encodes,
multiplexes, and/or digitizes the outgoing baseband data to
generate a processed baseband or IF signal. The RF transceiver 310
receives the outgoing processed baseband or IF signal from the TX
processing circuitry 315 and up-converts the baseband or IF signal
to an RF signal that is transmitted via the antenna 305.
[0058] The processor(s) 340 can include one or more processors or
other processing devices and execute the basic OS program 361
stored in the memory 360 in order to control the overall operation
of the client device 300. For example, the processor(s) 340 could
control the reception of forward channel signals and the
transmission of reverse channel signals by the RF transceiver 310,
the RX processing circuitry 325, and the TX processing circuitry
315 in accordance with well-known principles. In some embodiments,
the processor(s) 340 includes at least one microprocessor or
microcontroller.
[0059] The processor(s) 340 is also capable of executing other
processes and programs resident in the memory 360, such as
operations for unlocking an electronic device with an authenticated
wearable device. The processor(s) 340 can move data into or out of
the memory 360 as required by an executing process. In some
embodiments, the processor(s) 340 is configured to execute the
applications 362 based on the OS program 361 or in response to
signals received from external devices or an operator. The
processor(s) 340 is also coupled to the I/O interface 345, which
provides the client device 300 with the ability to connect to other
devices such as laptop computers and handheld computers. The I/O
interface 345 is the communication path between these accessories
and the processor(s) 340.
[0060] The processor(s) 340 is also coupled to the touchscreen 350
and the display unit 355. The operator of the client device 300 can
use the touchscreen 350 to enter data into the client device 300.
The display 355 may be a liquid crystal display or other display
capable of rendering text and/or at least limited graphics, such as
from web sites.
[0061] The memory 360 is coupled to the processor(s) 340. Part of
the memory 360 could include a random access memory (RAM), and
another part of the memory 360 could include a Flash memory or
other read-only memory (ROM).
[0062] As will be discussed in greater detail below, in this
illustrative embodiment, client device 300 implement an image
processing unit that receives encoded images or videos from server
104 over network 102 and decodes the 360 degree videos using region
adaptive smoothing and motion estimating and compensation for 360
degree video. Although FIGS. 2 and 3 illustrate examples of devices
in a computing system, various changes may be made to FIGS. 2 and
3. For example, various components in FIGS. 2 and 3 could be
combined, further subdivided, or omitted and additional components
could be added according to particular needs. As a particular
example, the processor(s) 340 could be divided into multiple
processors, such as one or more central processing units (CPUs) and
one or more graphics processing units (GPUs). Also, while FIG. 3
illustrates the client device 300 configured as a mobile telephone
or smartphone, client devices could be configured to operate as
other types of mobile or stationary devices. In addition, as with
computing and communication networks, client devices and servers
can come in a wide variety of configurations, and FIGS. 2 and 3 do
not limit this disclosure to any particular client device or
server.
[0063] FIG. 4 illustrates a 360 degrees video processing chain 400
from capture 405, to image stitching and equirectangular mapping
410, to video encoding 415, to video decoding 420, and rendering
1125. The 360 degree view of the world is typically captured using
multiple cameras. The capture 405 of FIG. 4 shows an example where
seven cameras are used. Five cameras covering the front, the back
and the sides, one camera on the top and one camera on the bottom.
Images from the multiple cameras are aligned, stitched together,
and equirectangularly mapped 410 into a single image.
[0064] FIGS. 5A-5D illustrate an example of stitching and
equirectangular mapping 510. FIG. 5A illustrates the seven images
500 from the seven cameras that are fed to the stitching process.
These inputs are generated by simulating the capture of
checkerboard images using a wide eye lens with horizontal field of
view of 122.6 degrees and vertical field of view of 94.4 degrees.
FIG. 5B illustrates the corresponding stitched image 505. The top
and bottom checkerboard patterns are from the top and bottom
cameras respectively. Each of the seven images in FIG. 5A are of
size 1920.times.1440. The stitched image 505 in FIG. 5B is of size
4096.times.2048.
[0065] The 360 degrees video at the output of the stitching process
is coded as regular 2D video by using standard video codecs such as
H.264/AVC and HEVC/H.265. During playback the compressed video can
be streamed or downloaded and decoded. After decoding, the video is
texture mapped onto a virtual sphere 510 in a 3D graphics
environment, as illustrated in FIG. 5C, with the viewer located at
the center of the virtual sphere 510. When the video in FIG. 5B is
viewed with a 360 degrees video viewer, the user gets a perception
of standing in a room with five walls and a ceiling and a floor.
FIG. 5D is a screen capture of the output 515 of a 360 degrees
video viewer that has been included in the figure to help
understand this perception.
[0066] Another observation is the top and the bottom views occupy a
larger number of pixels in the 360 degrees stitched image when
compared to the front, the back and the side views. This is evident
comparing FIG. 5B to FIG. 5C, where all the views cover roughly
equal areas on the sphere. This observation is a characteristic of
the equirectangular mapping and also exists in world maps that are
mappings of the surface of the globe (a sphere) to a 2D surface
(the map). In world maps, the land masses near the poles appear
much larger than the land masses near the equator. This disclosure
exploits this characteristic of the equirectangular mapping to
provide bitrate savings, smoothing the top and the bottom regions
of video before encoding. Since the pixels in the top and the
bottom part of the stitched picture have more resolution than what
is perceptually noticeable, the smoothing does not lead to
perceptual quality degradation. However, the smoothing results in
bitrate savings since smooth regions require transmitting fewer
transform coefficients.
[0067] FIG. 6 illustrates an equidistant mapping 600 between a
rectangular plain 605 and a warped plain 610. The rectangular plain
605 is in terms of x and y. The warped plain 610 is in terms of u
and v.
[0068] The warpings in a fisheye lens are non-linear mappings from
the rectangular plane to the warped plane 610. There are varieties
of models representing the mapping, and among those, the
equidistant mapping is most common.
r=f.theta., (eq. 1)
whereas demonstrated in FIG. 1, .theta. is the angle of a point
s(x,y) in the rectangular plane 605 to the plane center 615,
(x.sub.0, y.sub.0). The mapping result r is the distance between
the mapped point p(u,v) in the warped plane P to the warped plane
center 615, (u.sub.0, v.sub.0).
[0069] The mapping process is described as the following. Let d be
the distance between s to (x.sub.0,y.sub.0): d= {square root over
(((x-x.sub.0).sup.2+(y-y.sub.0).sup.2))}. The angle will be
.theta.=arctan(d/f). The warped distance is then r=f arctan(d/f).
Given the Homogeneous relationship between (x,y) in S to (u,v) in
P:
u r = x d , v r = y d ( eq . 2 ) ##EQU00001##
[0070] The mapping is written as
u = xf d arc tan ( d f ) and ( eq . 3 ) v = yf d arc tan ( d f ) (
eq . 4 ) ##EQU00002##
[0071] The inverse mapping from warped plane 615, P, to rectangular
plane 610, S, can be derived similarly (x,y)=iT(u,v):
.theta. = r f ( eq . 5 ) d = f tan ( .theta. ) = f tan ( r f ) ( eq
. 6 ) x = uf r tan ( r f ) and ( eq . 7 ) y = vf r tan ( r f ) ( eq
. 8 ) ##EQU00003##
[0072] FIG. 7A illustrates the effects 700 of warping after mapping
and FIG. 7B illustrates the effects 705 of warping before mapping.
The characteristic of the mapping is more warping is applied the
further the point is from the center.
[0073] FIG. 8A illustrates a motion estimation 800, where a PU 810
in current frame 815 f.sub.i is looking for a prediction candidate
block 820 from previously coded and reconstructed frame 825 f.sub.j
that has the same shape as current PU 810. The reference frame
index j and the motion vector .DELTA. will be encoded as motion
estimation parameters.
[0074] FIG. 8B illustrates a warped motion estimation 805. In the
rectangular space, the pixel p.sub.1 moves to the location of
p.sub.2, then all the other pixels in the PU will move with the
same MV, namely:
.DELTA.=s.sub.2-s.sub.1=s.sub.4-s.sub.3 (eq. 9)
[0075] However, the same motion relationship will not be maintained
in the warped plane. If a rectangular block in the warped plane
moved with motion vector .delta. that is not equal to zero, the
locations of the pixels within the rectangular block will no longer
maintain same relative position to the others. As demonstrated in
FIG. 8B, if p.sub.1 moves to the location of p.sub.2, then the
location where p.sub.3 moves to will not be
p.sub.3+p.sub.2-p.sub.1. However, the same motion relationship
should be maintained in the unwarped plane. As a result,
intermediate mappings and interpolation should be done.
[0076] The warped motion estimation problem is: Given a PU in the
frame f.sub.i which is indicated by the top-left pixel p.sub.1 in
the warped video sequence, if p.sub.1 moves to the location of
p.sub.2 in the other frame f.sub.j, what will another pixel p.sub.3
in the PU move to (i.e. what is the location of p.sub.4)?
[0077] By assuming the same motion relationship in the unwarped
plane, intermediate mappings 830 are used to compute the location
of p.sub.4 in the rectangular plane and map it back to the warped
plane. The mapping from rectangular plane S to warped plane P is
denoted by p=T(s), and the inverse mapping is denoted by s=T(p)
s.sub.1=iT(p.sub.1), s.sub.2=iT(p.sub.2), s.sub.3=iT(p.sub.3) (eq.
10)
.DELTA.=s.sub.2-s.sub.1 (eq. 11)
s.sub.4=s.sub.3+.DELTA. (eq. 12)
p.sub.4=T(s.sub.4)=T(s.sub.3+.DELTA.)=T(iT(p.sub.3)+iT(p.sub.1+.delta.)--
iT(p.sub.1)) (eq. 13)
[0078] FIG. 9A illustrates an interpolation 900 of mapped pixels
915 by pixels 920 in frame f.sub.j 925. Once all the pixel
locations after motion are obtained using the intermediate
mappings, the values of the pixels at those locations should be
determined by interpolation techniques.
[0079] A possible embodiment in this invention uses bilinear
interpolation for the Luma components and nearest neighbor
interpolation of the chroma components. The prototype experiments
shows that using bilinear interpolation in Luma components is much
advance than using nearest neighbor interpolation. Referring to
FIG. 9B, the two interpolation techniques are described as
following:
[0080] A pixel location (x,y) found by intermediate mappings must
resides in a cell between 4 neighboring pixels on the pixel grid.
Let x.sub.i=.left brkt-bot.x.right brkt-bot. and y.sub.i=.left
brkt-bot.y.right brkt-bot. be the integer part of (x,y)
respectively. t.sub.2=x-x.sub.i and t.sub.1=y-y.sub.i are the
coordinate differences. The nearest neighbor interpolation finds
the value of (x,y) by I(x,y)=I(nearest points on the grid to x,y),
whereas the bilinear interpolation finds the value of (x,y) by
I(x,y.sub.i)=(1-t.sub.1)I(x,y.sub.i)+t.sub.1I(x,y.sub.i+1) (eq.
14)
I(x,y)=(1-t.sub.2)I(x.sub.i,y.sub.i)+t.sub.2I(x.sub.i+1,y.sub.i)
(eq. 15)
I(x,y.sub.i+1)=(1-t.sub.2)I(x.sub.i,y.sub.i+1)+t.sub.2I(x.sub.i+1,y.sub.-
i+1) (eq. 16)
[0081] After interpolation, the interpolated pixel values are the
prediction of current PU.
[0082] FIG. 9C illustrates a motion vector predictor compensation
(MVPC) 910 according to various embodiments of the present
disclosure. In the inter prediction techniques, motion vector
prediction that reuses and encodes the difference between current
PU motion vector to one of the neighboring PU's motion vector have
great advantage for utilizing spatial coherence. However, in the
warped plane, because of the difference of PU locations, the
neighboring PU's motion vector should not be used directly, instead
compensation is added.
[0083] As illustrated in FIG. 9C, the MVPC requires the current
PU.sub.2 knows the offset .tau. of reference PU.sub.1 as well as
the motion vector .delta..sub.2 of PU.sub.1. Then the motion vector
prediction is .delta..sub.2 plus MVPC .gamma., where same motion
relationship in unwarped plane is revisited.
s 1 = iT ( p 1 ) , s 2 = iT ( p 2 ) ( eq . 17 ) p 2 = p 1 + .tau. (
eq . 18 ) p 4 = p 2 + .delta. 2 , .delta. 2 = p 4 - p 2 ( eq . 19 )
.DELTA. 2 = S 4 - S 2 = iT ( p 4 ) - iT ( p 2 ) ( eq . 20 ) s 3 = s
1 + .DELTA. 2 = S 1 + iT ( p 2 + .delta. 2 ) - iT ( p 2 ) ( eq . 21
) .delta. 1 = p 3 - p 1 = T ( iT ( p 1 ) + iT ( p 2 + .delta. 2 ) -
iT ( p 2 ) ) - p 1 ( eq . 22 ) .gamma. = .delta. 1 - .delta. 2 = T
( iT ( p 1 ) + iT ( p 2 + .delta. 2 ) - iT ( p 2 ) ) - p 1 - p 4 +
p 2 = T ( iT ( p 1 ) + iT ( p 1 + .tau. + .delta. 2 ) - iT ( p 1 +
.tau. ) ) - p 1 - .delta. 2 ( eq . 23 ) ##EQU00004##
[0084] FIG. 10 illustrates an additional warp mode 1000 in an RDO
search 1005 according to various embodiments of the present
disclosure. In certain embodiments, warp motion estimation mode
(including the MVPC) is added upon traditional inter prediction
techniques.
[0085] In this case, additional overhead must encoded to indicate
the extra warp mode. Two coding schemes are shown in Table 1.
TABLE-US-00001 TABLE 1 Overhead Coding Scheme 1 Scheme 2 Encoder
... ... encode skipFlag encode skipFlag if ( skipFlag) if (
skipFlag) encode warpFlag encode warpFlag encode mergeIndex encode
MergeIndex else else if ( mode = MODE_INTRA) if ( mode =
MODE_INTER) encode 0 encode 0 else if (mode = MODE_INTER) else if
(mode = MODE_INTRA) encode 1 encode 1 encode 0 for no warp encode 0
else // the case of MODE_INTER_WARP else // the case of
MODE_INTER_WARP encode 1 encode 1 encode 1 for warp encode 1 endif
endif encoder inter pred parameters encoder inter pred parameters
endif endif .... .... Decoder ... ... decode skipFlag decode
skipFlag if (skipFlag) if (skipFlag) decode warpFlag decode
warpFlag if (warpFlag) if (warpFlag) setPredMode(MODE_INTER_WARP)
setPredMode(MODE_INTER_WARP) else else setPredMode(MODE_INTER)
setPredMode(MODE_INTER) endif endif decode mergeIndex decode
mergeIndex else else decode flag decode flag if (flag) if (flag)
decode warpFlag decode warpFlag if (warpFlag) if (warpFlag)
setPredMode(MODE_INTER_WARP) setPredMode(MODE_INTER_WARP) else else
setPredMode(MODE_INTER) setPredMode(MODE_INTRA) endif endif else
else setPredMode(MODE_INTRA) setPredMode(MODE_INTER) endif endif
endif endif ... ...
[0086] Look-up tables are used to reduce the computation table. Two
aspects that significantly affect the complexity of the warping are
mapping functions and distance computation. The distance between
the plain center to the pixels on the grid may not change for all
the frames, so the distances are pre-computed and stored to a 2D
array that is the same size as the video frame.
[0087] In the mapping function, the most expensive calculation is
finding the value of tan( ) and arctan( ). In certain embodiments,
the values are quantized and stored with limited precision. For
example, the distance between two adjacent pixels is one
(normalized). Then the smallest nonzero difference between two
distance is:
.lamda. = 2 - 1 4 f , ( eq . 24 ) ##EQU00005##
where 2 is the distance of diagonal pixels, 1 is the distance of
adjacent pixels, f is the focal length in unit of pixels and 4
represent the smallest fractional 1/4 in the motion estimation. The
quantized values for forward mapping are:
tan ( x ) , where x = 0 , .lamda. , 2 .lamda. , , .pi. 2 ( eq . 25
) ##EQU00006##
[0088] and the values of inverse mapping are:
arctan(x), where x=0,.lamda.,2.lamda., . . . ,.pi. (eq. 26)
[0089] Table 2: BD Rate comparison in low delay P configuration
between HM14 (with fractional motion estimation disabled) to warped
motion estimation as an extra mode (proposed). Negative values mean
gain. The first 7 rows are natural sequences which are downsampled
and warped before coding. The last 3 rows are simulated global
motion (with motion speed n pix/frame) and warped.
TABLE-US-00002 Seq. Name BD Rate Ave
BasketballDrillText_wrap_640x360_50 -3.8% -1.4%
BQTerrace_wrap_640x360_60 -1.5% Cactus_wrap_640x360_50 -0.4%
ParkScene_wrap_640x360_24 -0.9% Kimono_wrap_64x360_24 -0.7%
City_wrap_512x256_60 -1.9% Crew_wrap_512x256_60 -0.6%
bask1_wrap_640x360_24 (8 pix/frame) -8.2% -9.3%
bask2_wrap_640x360_24 -14.1% (16 pix/frame) bask3_wrap_640x360_24
(4 pix/frame) -5.6%
[0090] FIG. 11 illustrates the 360 degrees video processing process
1100 with such a region adaptive smoothing 1115 according to
various embodiments of the present disclosure.
[0091] The capture 1105 takes the images from seven different
cameras. The images 1110 from the seven cameras are ordered in a 2D
pattern. The image stitching and equirectangular mapping 1110 takes
the images and combines them into an equirectangular map 1120.
[0092] The region adaptive smoothing 1125 is a pre-processing step
at the encoding side and not dependent on the type of the codec,
hence it can be easily supported using existing codecs.
[0093] To test the impact of smoothing, a 7.times.7 Gaussian filter
(with variance of 5) was used to smooth eleven different 360
degrees videos listed in Table 3. The top and bottom pSmooth, the
percentage of the top region 1130 and bottom region 1135 of the
image that are smoothed, percent of all the images in the video
sequences was smoothed and encoded using a .times.264 (random
access setting with QP=27) to determine the bitrate savings. The
bitstreams corresponding to Subway, Zoo, and DragonRide2, with and
without smoothing, were also formally viewed using a GEARVR to
determine the pSmooth value at which the perceptual quality
degradations start becoming visible. Subway and Zoo sequences are
natural sequences whereas DragonRide2 is a computer generated
animation. For natural video sequences, the perceptual quality
degradation starts becoming slightly noticeable at pSmooth equal to
twenty percent, while for computer generated animation the
perceptual quality degradation starts becoming slightly noticeable
at pSmooth equal to fifteen percent. This observation roughly holds
for other video sequences that were informally viewed. Table 3
below shows the bitrate saving for pSmooth equal to twenty percent
and fifteen percent. It can be seen that bitrate savings in the
range of four to twenty two percent is achieved with the present
region adaptive smoothing technique.
TABLE-US-00003 TABLE 3 pSmooth = pSmooth = 20% 15% Natural video:
AirPlane_4096x2048_30fps_P420 18.8% 13.4%
BikeRide_4096x2048_30fps_P420 8.3% 3.2% Bridge_4096x2048_30fps_P420
8.8% 5.4% Canal_4096x2048_30fps_P420 4.0% 2.4%
DART_4096x2048_30fps_P420 15.2% 7.8% MonoTrain_4096x2048_30fps_P420
5.5% 3.3% Plaza_4096x2048_30fps_P420 16.5% 11.1%
Subway_4096x2048_30fps_P420 20.5% 13.5% Zoo_4096x2048_30fps_P420
22.7% 13.2% Computer animation: DragonRide1_1920x1080_30fps_P420
16.3% 10.7% DragonRide2_1920x1080_30fps_P420 21.7% 14.6% Average
14.4% 9.0%
[0094] Once the equirectangular mapped image 1115 is smoothed, the
equirectangular mapped image 1115 is encoded 1140 for transmission.
The equirectangular mapped image 1115 is received by a decoder and
decoded 1145. Once the equirectangular mapped image 1115 is
decoded, an image processing unit renders 1150 the equirectangular
mapped image 1115 into a sphere 1155. The sphere 1155 is then used
by the viewer 1160 to see the 3D image or video 1165.
[0095] Another observation from FIG. 5B is the image is stretched
more toward the top and the bottom of the image, allowing an
increase the degree of smoothing at the top and the bottom of the
image without increasing perceptual loss. The degree of smoothing
is controlled by increasing the variance of the Gaussian smoothing
filter near the top and the bottom of the image. FIG. 12A
illustrates the normalized sphere with a radius of one that is used
to derive the heuristics for calculating the variance of a Gaussian
smoothing filter as a function of the image row number y. At the
image row number y, the inherent resolution of the image on the
sphere is proportional to x, i.e. {square root over (1-y.sup.2)}.
As y increases to the top pole, x keeps decreasing (similarly as y
decreases to the bottom pole, x keeps decreasing). However, the
equirectangular mapping still uses the full width of the image to
represent this resolution. Hence, the following equation that is
inversely proportional to {square root over (1-y.sup.2)} is used to
determine the variance .sigma..sup.2 of Gaussian smoothing
filter
.sigma. 2 = K - K 1 - y 2 ( eq . 1 ) ##EQU00007##
[0096] As y goes from zero, the center of the image, to one, the
top of the image, .sigma..sup.2 goes from zero to a large value,
i.e., no smoothing to very strong smoothing. FIG. 12B illustrates
how .sigma..sup.2 varies with the normalized image row number
(normalized to be between negative one, which is bottom of the
image, to positive one, which is the top of the image) for K equal
to three. Variable smoothing was implemented in .times.264. Table 4
shows the corresponding bitrate savings which are higher than those
of Table 3. By increasing K, we found variable smoothing especially
useful at low bitrates, with rate control enabled, since the center
region of the image is slightly smoothed to achieve additional
bitrate savings.
TABLE-US-00004 TABLE 4 Variable smoothing (K = 3) Natural video:
AirPlane_4096x2048_30fps_P420 26.0% BikeRide_4096x2048_30fps_P420
18.3% Bridge_4096x2048_30fps_P420 13.8% Canal_4096x2048_30fps_P420
9.3% DART_4096x2048_30fps_P420 25.9% MonoTrain_4096x2048_30fps_P420
16.9% Plaza_4096x2048_30fps_P420 26.9% Subway_4096x2048_30fps_P420
28.6% Zoo_4096x2048_30fps_P420 35.3% Computer animation:
DragonRide1_1920x1080_30fps_P420 23.2%
DragonRide2_1920x1080_30fps_P420 27.9% Average 22.9%
[0097] FIG. 13 illustrates a process for coding of 360 degrees
videos using region adaptive smoothing according to various
embodiments of the present disclosure. For example, the process
illustrated in FIG. 13 may be performed by the server 200 in FIG.
2.
[0098] In step 1305, the image processing unit defines the top
region and bottom region of the equirectangular mapped image or
each of the equirectangular mapped frames of a video. The top
region and bottom region can be predefined or based on a function
such as amount of information in a region.
[0099] In step 1310, the image processing unit selects a row and
determines if the row is in the top region or the bottom region. In
step 1315, the image processing unit performs a smoothing process
on the row of pixels when the row is in the top region or the
bottom region. In step 1320, the image processing unit determines
if there are any remaining rows in equirectangular mapped image or
each of the equirectangular mapped frames of the video.
[0100] FIG. 14 illustrates a process for coding of 360 degrees
videos using row position for a strength of the region adaptive
smoothing according to various embodiments of the present
disclosure. For example, the process illustrated in FIG. 14 may be
performed by the server 200 in FIG. 2.
[0101] In step 1405, the image processing unit defines the top
region and bottom region of the equirectangular mapped image or
each of the equirectangular mapped frames of a video. The top
region and bottom region can be predefined or based on a function
such as amount of information in a region. In step 1410, the image
processing unit selects a row and determines if the row is in the
top region or the bottom region.
[0102] In step 1415, the image processing unit determines the
strength of smoothing to use depending on the row position. The
rows at the top and bottom of the equirectangular mapped image have
the same amount of pixels as the other rows in the map, but
represent a much smaller amount of pixels on the sphere. Therefore,
when the sphere is rendered, the north and south poles include more
information than was actually captured. Because of this effect of
equirectangular mapping, the strength of the smoothing increases as
the rows approach the top and bottom of the equirectangular mapped
image. The strength of the smoothing can be determined based on a
ratio between the amount of pixels in the row and the amount of
pixels in the corresponding portion or line of latitude of the
virtual sphere.
[0103] In step 1420, the image processing unit performs a smoothing
process on the row of pixels when the row is in the top region or
the bottom region. In step 1420, the image processing unit
determines if there are any remaining rows in equirectangular
mapped image or each of the equirectangular mapped frames of the
video.
[0104] FIG. 15 illustrates a 360 degrees video processing chain
according to various embodiments of the present disclosure. In
addition to the process in FIG. 11, the encoder transmits smoothing
metadata 1505 to the decoder for extra detail enhancement 1510. The
smoothing metadata comprises smoothed region information including
bounding box coordinates and smoothed filtering information
including a filtering type, a filtering strength, and whether fixed
or variable smoothing was used. Transmitting the smoothing metadata
allows for greater smoothing in the equirectangular mapped image.
The detail enhancement includes methods such as edge enhancement
and inverse filtering.
[0105] FIGS. 16A and 16B illustrate alternative smoothing regions
according to various embodiments of the present disclosure. Along
with smoothing a top region 1600 and a bottom region 1605, a left
region 1610 and a right region 1615 can also be smoothed. The
different regions can by asymmetrical, as in an asymmetrical top
region 1625 and an asymmetrical bottom region 1630. In certain
embodiments, the corners are smoothed at an angle. The purpose of
the alternative smoothing regions is to increase the bitrate of the
transfer, while minimizing the perceptual loss.
[0106] FIG. 17 illustrates squeezing the top region 1705 and bottom
region 1710 of an equirectangular mapped frame 1700 according to
various embodiments of the present disclosure.
[0107] Because the top region 1705 and bottom region 1710 of the
equirectangular mapped frame contain a higher resolution than what
is perceptually noticeable, these regions can be squeezed before
encoding to reduce the amount of transform coefficients to be
transmitted resulting in bitrate savings. The squeezed top region
1720 and squeezed bottom region 1725 of the squeezed
equirectangular mapped frame 1715 do not lead to perceptual quality
degradation when viewed. The squeezing can be uniform across the
top region 1705 or the bottom region 1710. For example, the
down-sampling ration of the top twenty percent of the image can be
uniform as 2. The squeezing can also be adaptive depending on the
resolution of the top region 1705 or bottom region 1710. For
example, if the top ten percent of the equirectangular frame
contains a lower resolution that the ten to twenty percent of the
equirectangular frame 1700, the top ten percent could have a
down-sampling ratio of 4 while the higher resolution portion of the
top region 1705 could have a down-sampling ratio of 2.
[0108] Although the present disclosure has been described with an
exemplary embodiment, various changes and modifications may be
suggested to one skilled in the art. It is intended that the
present disclosure encompass such changes and modifications as fall
within the scope of the appended claims.
* * * * *