application note - video mos on youtube

8/20/2019 Application Note - Video MOS on YouTube

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SwissQual®... QualiPoc & DiversityVideo MOS on Android YouTube

Application Note

A p p l i c a t i o n N o t e

8002667883 ─ 01(Þ2ÐÜá)

T e s t & M e a s u r e m e n t


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ContentsSwissQual ... QualiPoc & Diversity

3 Application Note 8002667883 ─ 01

Contents

1 Introduction............................................................................................ 51.1 A Short History of YouTube.........................................................................................5

1.2 Measurement Considerations......................................................................................6

2 Video Compression and Resolution on YouTube...............................7

2.1 YouTube App Versions.................................................................................................8

2.2 Streaming With DASH...................................................................................................8

2.3 YouTube App Versions That Use DASH................................................................... 11

3 Video Quality Testing in YouTube......................................................12

4 Implementation of Video-MOS in QualiPoc....................................... 14

4.1 New ITU-T J.343.1 Standard....................................................................................... 14

4.2 Using J.343.1 for YouTube Tests...............................................................................14

4.3 Handling of Freezing, Still Images, and Black Frames............................................16

4.4 Example YouTube Video Quality Examples............................................................. 17

4.5 Compatibility............................................................................................................... 18

Annex.................................................................................................... 19

A Customer Support Center................................................................... 19


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ContentsSwissQual ... QualiPoc & Diversity



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IntroductionSwissQual ... QualiPoc & Diversity


1 Introduction

YouTube is moving away from a pure video-streaming platform that streams uploadedvideos to an application on a smartphone or a PC. YouTube has become a complex

and interactive portal that provides additional information prior and parallel the video.

The video itself is delivered in different qualities according to access technology. You-

Tube encrypts video transmission and uses DASH now to react dynamically to availa-

ble network capacity by reducing or increasing the video bitrate. This approach leads

to variable video quality and targets the best trade-off between compression and freez-

ing , that is, preferring a slightly blurry video to a stalled video.

Consequently, testing and measuring the YouTube video streaming service has

become more complicated. The change of the YouTube session structure moves away

from the sequential step-by-step buildup as assumed in standard measuring proce-

dures. As a result, some trigger-points as defined by ETSI are either no longer accessi-

ble through encryption or now have a different meaning due to the different session

structure. SwissQual now focuses on events that are visible to a viewer to provide a

more customer oriented, flexible, and future-proof solution.

Bitstream encryption is not the only challenge. YouTube also scales down the resolu-

tion and changes the spatial compression of a video based on access technology and

network capacity. The YouTube client requests video chunks in a quality that is appro-

priate to the current channel capacity. Pre-buffering is scaled up in high capacity situa-

tions and video chunks are re-loaded when the network improves. All of these changes

render the mean video bitrate obsolete as an indicator of video quality. Hence a high

quality algorithm that considers all of these impacts is required.

SwissQual has integrated a real visual quality measure that combines bitstream infor-mation with image information to consider what the viewer actually sees. The imple-

mented measure is the ITU-T J.343.1 standard from 2014, which is the first image-

based no reference model that has been standardized in ITU-T. The ITU-T J.343.1

algorithm is available on QualiPoc Android and has been designed for video streaming

services that use encrypted streams. This lean algorithm combines image and IP

header information to predict Video Mean Opinion Scores (MOS) and is perfectly tail-

ored for use on smartphones.

By introducing this Video MOS for YouTube video streaming, SwissQual emphasizes

and proves its leadership in applied research and Android development in order to

handle the latest technology trends.

1.1 A Short History of YouTube

When YouTube started out it was a passing hosting platform where people uploaded

and shared private video streams. YouTube prepared the videos for streaming to

Adobe’s Flash Player, which was the prevalent browser plug-in streaming client. The

proprietary video container was later changed to MP4, while the first mobile applica-

tions were served 3GP video streams. The compression codecs were MP4 and H.264.

The basic approach was to compress and stream the video continuously.

A Short History of YouTube


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IntroductionSwissQual ... QualiPoc & Diversity


Since networks could not deliver constant throughputs, YouTube, along with other

video on demand services, implemented a progressive download strategy to avoid

interruptions in the video stream. This strategy created a buffer which stored the parti-

ally downloaded video stream before the playout started and to bridge gaps that wouldhave occurred in the absence of new packets. The determination of buffer length con-

tinues to be a topic of optimization.

YouTube soon became interesting to professional and semi-professional content pro-

viders and its content grew rapidly. The YouTube platform was extended to include

additional information, such as advertisements and the listing of the most watched vid-

eos.

Technological advances since YouTube's inception have resulted in more people view-

ing its content on mobile YouTube apps than on traditional PC player base.

YouTube has been moving away from streaming single MP4 files, where the entire clip

was encoded with at a specific bitrate, to hosting the same video clips at different reso-

lutions, including other transmission technologies. YouTube recently introduced

Dynamic Adaptive Streaming over HTTP (DASH) and has started a transition to other

video codecs.

YouTube still provides the older formats and continues to support players and smart-

phone Apps that have not been updated for years. That is, each video is available in

several formats and based on the requesting application, YouTube streams the match-

ing format. Even today, RTSP streams from the early days are accessible, but in a

reduced number of resolutions. This approach leads to the fact that for the same

requested video, physically very different streams are delivered to different player or

mobile App versions.

1.2 Measurement Considerations

The YouTube player version along with the technologies that are used on the YouTube

server side are an important consideration for video quality measurement. The You-

Tube streaming process includes many influences on quality that are completely inde-

pendent of the user and measurement gear.

The composition of the server’s current technology, the network, and the player’s capa-

bilities are always evaluated during the measurement. Measurement results provides a

snapshot at the time of the measurement. However, even under the same networkconditions, the measured quality can be different at a different point in time if the tech-

nology has been changed or if the support of individual players becomes restricted.

Measurement Considerations


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Video Compression and Resolution on YouTubeSwissQual ... QualiPoc & Diversity


2 Video Compression and Resolution on You-

TubeFor a long time YouTube encoded video streams in a target bitrate for a given resolu-

tion, for example, around 500kbit/s for a 360p video clip. This principle was not

changed with the introduction of different container formats. Starting with HD content,

the video container was MP4 and the lower resolutions were changed from Flash FLV

to 3GP, a derivative of MP4 that was optimized for mobile transmission.

YouTube transcoded each uploaded video to all of the supported formats and resolu-

tions and then stores the files on YouTube servers. The resolution of the video screen

remained constant in the stream while its size depended on the type of player. For

example, the Flash player on a PC allowed you to select the resolution, while mobile

clients tended to be served with a fixed (low) resolution.

Player

720p

480p

360p

240p

YouTube

Video upload(for example,

HD720)

Downstream(for example,

360)

User client

Display

Transcoding

Figure 2-1: Schematic of YouTube streaming using a fixed resolution

When YouTube switched to HTTP/TCP transmission bit-errors that lead to heavily

impaired images stopped occurring. The only remaining problem was a potential inter-

ruption of the video stream that could not be bridged by the pre-buffered video. Such

an interruption froze the video until the packets were received again.

This was the reality for a few years. The video quality could be estimated quite well by

the bitrate and by counting the freezing effects on the screen under the assumption

that the resolution remained constant. This idea is reflected in ETSI TR 101 578 where

compression quality is considered constant and freezing the only problem.

Since then YouTube has introduced the next adaptation where video resolution, that is,image size and compression strength, was adjusted to the access technology for

mobile devices. In this adaptation, the access technology, that is, the server and the

player decide on the quality to be delivered.


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Player

720p

480p

360p

240p

YouTube

Video upload

(for example,HD720)

WLAN Mobile user client'YouTube App'

Re-scaling tophone display

LTE

2G / 3G

Transcoding

Figure 2-2: Schematic of YouTube selecting a fixed resolution streaming based on access technol-

ogy

The first resolution that was offered to mobile users was 240p, which was later

increased to 360p. LTE clients can also receive 480p and even HD content on request.

2.1 YouTube App Versions

The strategy that has been described so far was implemented in YouTube Apps ver-

sions 4.1, 4.2, and up to the beginning of the 5 series. To provide a user with some

control, one can specify a setting to request a higher quality stream. When this setting

is enabled, the App requests the next highest resolution, for example, in 2G/3G 360p

instead of 240p and 720p for LTE. This YouTube App setting remains enabled until it is

changed again.

The main difference between versions 4 and 5 of the YouTube App is the permanent

use of the HTTPS starting with version 5 instead of unencrypted HTTP. HTTPS

encryption makes it impossible to legally retrieve information from the TCP and HTTP

layer for quality measurements. As a result of the encryption, some of the typical trig-

ger-points for legacy HTTP streaming, as described by ETSI, are no longer accessible.

Consequently, the KPI calculation is now based fully on events that are visible by a

user instead of TCP packet analysis.

2.2 Streaming With DASH

In 2014, starting with YouTube App 5.7, YouTube introduced the new video container

DASH. DASH is the basis for adaptive streaming where video compression and resolu-

tion are adapted in 'real time'. DASH also enables reactions to network capacity prob-

lems by lowering the video bitrate on request.

In principle, the video is available in different resolutions on the server as it was in the

past. However, the video client no longer requests ‘just the video’, but rather requests

the stream piece-wise, for example, in chunks of a few seconds, and with a dedicated

resolution or bitrate. This technique allows asking for an individual resolution for each

requested piece of video. If the player derives information on the network capacity from

the received stream, for example, when looking at packet delays, this information can

Streaming With DASH


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be used to request lower resolutions when transmission capacity problems occur or to

step up to a higher resolution in case of performant networks.

DASH only enables the request of different resolutions whereas adaptivity to the net-

work is a feature of the YouTube player.

Player

720p

480p

360p

240p

YouTube


HD720)

Transcoding

Control

Mobile user client'YouTube App'


DASH

Figure 2-3: Scheme of YouTube streaming with DASH

Switching to this approach, the YouTube client on a PC or a mobile can use network

conditions to decide whether the next piece of video should be requested in a lower

resolution to ensure the transmission in time or to request more pieces in a higher

quality and higher bitrate to fill up the buffer under good network conditions.

The YouTube algorithm considers many features to achieve an optimal perceived qual-

ity. It can control which video quality is requested and for how long as well as the buffer

management.

The goal is to find the best trade-off between the following considerations:

● Short pre-buffering and re-buffering to ensure that video playback starts in a shorttime

● Avoid freezing

● Highest possible resolution

● Data caps and network load rules

This trade-off is illustrated in Figure 2-4 which shows the buffer status and the reload in

case of improved network conditions.

Streaming With DASH


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Constant low bitrate

240p

Network capacityNo Freezing Low compression quality Low network load

Constant high bitrate

480p

Potentially Freezing High compression quality High network load

Variable bitrate

Network capacityMinimized Freezing Best compression quality Optimal network load

360p360p

480p

720p

Figure 2-4: Principle transmission of low, high and adaptive bitrate

The use of a constant low rate will minimize freezing since a low rate can pass even

under low capacity; however, the perceived video quality is low due to the strong com-

pression even in high capacity situations.

A constant high rate delivers good visual quality if the network is able to transport the

stream, but there is a high risk of freezing and a high network load in low capacity

infrastructure.

Finally, the adaptation of the bitrate also minimizes freezing and delivers the best pos-

sible quality. There also means to further restrict the network load for low capacity net-

works.

The use of DASH possibilities is just starting. Current YouTube mobile Apps request a

resolution based on access technology only and do not rapidly switch the resolution in

Streaming With DASH


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response to changing network conditions. However, this is expected soon and all capa-

bilities are on board already.

2.3 YouTube App Versions That Use DASH

DASH as a protocol was introduced with YouTube App 5.7 in 2014. In version 5.10, a

change from HTTPS using open SSL to the 'speedy protocol' was made. As of March

2015 the latest YouTube App is 10.8. The adaptation is still restricted to the access

technology, that is, there is no variation of resolution when streaming to a mobile You-

Tube App. However, a change to encrypted HTTP 2.0 and the full use of variable

bitrate is expected soon.

YouTube App Versions That Use DASH


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Video Quality Testing in YouTubeSwissQual ... QualiPoc & Diversity


3 Video Quality Testing in YouTube

The perceived video quality for YouTube is determined by the applied compressionscheme, the strength of compression, and the potential freezing due to interruptions in

video delivery. Since HTTP/TCP is used as a safe transmission protocol, the received

packets are error free. By contrast, other video-telephony services as well as some

IPTV services that use RTP/UDP because of latency reasons, can have a UDP data-

gram with bit errors that lead to artefacts during decoding.

Based on the assumption of safe and error-free transmission most people have in You-

Tube, the video quality is determined by the loss of details during compressions along

with the occurrence of freezing because of an interrupted packet flow. Since freezing

can be viewed on the screen, it is easy to detect and to measure. The average bitrate

can also be measured and provides information about the compression strength.

However, there is no direct relationship between the compression ratio, that is, howstrong the original image information is compressed, and the visible quality. Individual

codecs have an individual efficiency, which determines how many details can be

pressed into a given data array. The state-of-art codec ITU-T H.264 can encode much

more details in a data structure than the previous H.263 codec and will soon be sur-

passed by the upcoming H.265. The new codec can achieve the same quality at H.264

with less data and lower bitrates.

Even the H.264 codec, which is widely used in streaming and TV services, supports

different profiles that can lead to different quality even if the video content and the ach-

ieved bitrate is the same.

If there is no variation in the codec and its profiles and if the evaluated video is the

same and is encoded at the same resolution, the average bitrate provides an idea

about the visual quality for a video with medium complexity.

In previous evaluations of YouTube streams, the compression ratio was constant and

quality evaluation at the fixed resolution could be restricted to freezing events only.

With the introduction of different resolutions, and thus bitrates, access technology

made this simple quality estimation unusable.

An HD session with a certain amount of freezing leads to a completely different per-

ception of the same stream in 240p with the same freezing. Simply looking for Freezing

makes it impossible to draw conclusions about video quality across different technolo-

gies. This is a serious problem in benchmarking when operator A has 60% LTE while

delivering HD content as compared to operator B which has almost no LTE andinstead delivers blurry pictures in 240p.

It is even more complicated if the bitrate and the resolution changes within a stream as

is the case with adaptive streaming. The pure bitrate becomes an unreliable indicator

of perceived compression quality. Even an average bitrate is unreliable as there is no

evidence that all retrieved video packets are actually decoded and displayed. Often,

overlapping parts are streamed down in different resolutions, but only one is finally dis-

played. The strategy, that is, what is displayed and how, and whether a post-process-

ing is applied or not, is defined by the decoder at the user side and cannot be seen in

the bitstream.


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Video Quality Testing in YouTubeSwissQual ... QualiPoc & Diversity


As a result, a reliable estimation of video quality is only possible if the quality measure

analyses the video frames that are actually displayed and takes into account informa-

tion from the decoded images. This is the reason why a video-quality measure that

examines the received bitstream and the image information is now integrated in theSwissQual YouTube testing approach.


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Implementation of Video-MOS in QualiPocSwissQual ... QualiPoc & Diversity


4 Implementation of Video-MOS in QualiPoc

4.1 New ITU-T J.343.1 Standard

The basis for the Video MOS prediction is the recently approved J.343.1 ‘RS-T-VMo-

del’. J.343.1 analyzes the incoming bitstream for the video client and observes the

resulting video at the same time. A video quality score is estimated based on informa-

tion taken from the bitstream, such as the size of a compressed frame, and the visual

impression of the decoded and displayed video frame and its temporal flow.

J.343.1 is a no-reference method that only analyzes the video on the receiving end and

not the input video at the transmitting side. This makes J.343.1 very flexible. It can be

used for live TV or video telephony applications and is especially designed for encryp-

ted bitstreams where access to the payload is not possible.

VideoSource

Encoding

TranscodingMPX

Decoder Player

J.343.1Meta information

IP

No information aboutreference video required

Figure 4-1: Principle measurement points of J.343.1

Lastly, J.341.1 is not dependent on one video resolution and contrary to previous video

quality measures, J.343.1 can produce quality scores on any resolution up to 1080p

HD content. This algorithm is perfectly suited for the variable bitrates and resolutions

that YouTube now uses.

4.2 Using J.343.1 for YouTube Tests

Technically, the algorithm is directly implemented in Android and runs on the smart-

phone in real-time. While the YouTube test is running, the algorithm has access to the

video bitstream, the decoded and displayed video frames, and runs a real-time analy-

sis for each frame. The Video MOS is then calculated for all frames in a time interval of

approximately 10 seconds.

One advantage of J.343.1 is its focus on one display size, which allows inter-resolution

comparisons. In the YouTube J.343.1 implementation, each video is analyzed video

and scored as it would be watched on a 1080p HD screen. This allows the algorithm to

Using J.343.1 for YouTube Tests


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be used precisely in a mobile streaming use case on a smartphone. Despite the video

resolution delivered by the YouTube server, the native video drivers on the smartphone

scale the received video frames up to the phones resolution. This is what the user

sees. The video quality algorithm does the same, that is, it receives a video in a certainresolution and rates the video as if it were scaled to 1080p. This fixed upscaling allows

you compare video in different delivered resolutions and from smartphones with differ-

ent display sizes.

Player

720p

480p

360p

240p

YouTube


HD720)

Transcoding

Control Mobile user client'YouTube App'


DASH

Server Network Smartphone

Video Quality J.343.1

MOSmodelling

Upscaling to 1080p

Image analysis

Bitstream meta information

Figure 4-2: Integration of J.343.1 for YouTube streaming on smart phones

The J.343.1 algorithm calculates and stores the Video MOS every few seconds and

stored. Since a YouTube session is longer than a few seconds, a series of Video MOS

values that describe the quality profile for the stream are available by the end of the

stream. This series show how the Video MOS values change over time and how it is

adapting to network conditions.

It has to be mentioned that this division of the stream into shorter parts for evaluation is

made in a very sophisticated way. It can be imagined as subsequently cutting the video

every few seconds instead of hard cuts every 10 seconds. The evaluation points are

chosen with some flexibility based on the content. Preferred MOS evaluation points are

when the resolution changes or a scene cuts to another scene. In case there is a pre-

ferred cutting point in this range, the next evaluation starts before a full synch frame is

cut.

Using J.343.1 for YouTube Tests


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240p

360p

480p

720p

Low

MOS

High

Avg MOS

Figure 4-3: Principle of long-term MOS profile over a stream

As a next integration step, the weighted average Video MOS for the entire stream is

provided and can be used for direct quality comparison of different YouTube streaming

sessions.

4.3 Handling of Freezing, Still Images, and Black Frames

The difference between freezing and a still image is that freezing is unwanted and not

part of the source video. The video displays pauses, and since no new information is

arriving, the last frame remains on display for a longer time until video playback

resumes.

A still image is simply non-moving video content and an intentional part of the video.

The image can be a capture of a still scene before something happens or an insertion

of a logo, a phone number, or an address, which is common on YouTube.

A human viewer can easily differentiate between freezing and a still image, but a pure

image-based no-reference model cannot. This is a huge advantage for J.343.1. When

there is no movement on the screen, the parallel analysis of the incoming bit-stream

Handling of Freezing, Still Images, and Black Frames


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allows it to differentiate between freezing (no new frames arriving) and still images

(new frames are arriving but the content is the same). This differentiation is unique for

no-reference models and enables safe freezing detection.

Another special effect in streaming video is frames without visible content, that is, asequence of black/very dark/mono-color frames or frames with barely visible content.

Such frames are marked but are not counted as an impairment since they belong to

the video content. They are even taken into account in the analysis of the frame rate or

the inter-frame difference.

The mono-color frames can also be white, for example, when very bright light leads to

white frames or for the blue frames introduced for synchronization in SwissQual refer-

ence videos.

4.4 Example YouTube Video Quality ExamplesSince video quality is calculated under the assumption that the received video is dis-

played on a 1080p HD mobile screen, video received at a smaller resolution is up-

scaled to 1080p. The visual quality of a 1080p video without any visible coding distor-

tions on such a screen is excellent, while a 720p video is a bit blurry due to it contain-

ing less spatial information in 720 lines than in 1080 lines. When a 360p or a 240p

video is up-scaled, the resulting picture is very blurry, even without any coding arte-

facts.

If a video is streamed from YouTube, coding impairments due to strong compression

are also present visible in addition to the pure reduction of resolution. This leads to a

further loss of spatial details so that the achieved quality in YouTube streaming tests islower than the maxima for a given resolution.

Table 4-1 presents some Video MOS ranges from tests performed at the beginning of

2015. The Video MOS is highly dependent on the content and the ranges must be

seen as an orientation for a medium complex video.

Table 4-1: Video MOS ranges

Resolution w/o coding distortions Typical on YouTube

240p ~3.0 2.0 - 2.8

360p ~3.6 2.5 - 3.3

480p 4.3 3.6 - 4.1

720p 4.6 3.8 - 4.2

1080p 4.8 4.2 - 4.5

If an arbitrary video from YouTube is selected, the resolution of the content and the

image might not match the resolution. Quite often widescreen videos are provided that

contain black bars at the top and bottom as known from TV. Therefore, even if a video

is flagged as 360p, the image height might only be 290 lines. This obviously influences

the video MOS and the stream will receive a score closer to a 240p video than a 360p

video.

Example YouTube Video Quality Examples


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4.5 Compatibility

The support of Video MOS on YouTube depends on the low-layer video driver and its

accessibility as well of the Android version of the phone. As a result, not all SwissQualQualiPoc and Diversity 15.3 devices can provide Video MOS values.

For a list of compatible phones see the Diversity and QualiPoc 15.3 Release Notes or

contact our support center.

Please consult Chapter A, "Customer Support Center", on page 19 for the best

method to contact us.

Compatibility


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Customer Support Center SwissQual ... QualiPoc & Diversity


Annex

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tomer Support Centers. A team of highly qualified engineers provides telephone sup-

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Up-to-date information and upgrades

To keep your instrument up-to-date and to be informed about new application notes

related to your instrument, please send an e-mail to the Customer Support Center stat-

ing your instrument and your wish. We will take care that you will get the right informa-

tion.

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application note - video mos on youtube

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