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• WebVTT Discussions at FOMS

  18 décembre 2013, par silvia

  At the recent FOMS (Foundations of Open Media Software and Standards) Developer Workshop, we had a massive focus on WebVTT and the state of its feature set. You will find links to summaries of the individual discussions in the FOMS Schedule page. Here are some of the key results I went away with.

  1. WebVTT Regions

  The key driving force for improvements to WebVTT continues to be the accurate representation of CEA608/708 captioning. As part of that drive, we’ve introduced regions (the CEA708 “window” concept) to WebVTT. WebVTT regions satisfy multiple requirements of CEA608/708 captions :

  1. support for rollup captions
  2. support for background color and border color on a group of cues independent of the background color of the individual cue
  3. possibility to move a group of cues from one location on screen to a different
  4. support to specify an anchor point and a growth direction for cues when their text size changes
  5. support for specifying a fixed number of lines to be rendered
  6. possibility to specify which region is rendered in front of which other one when regions overlap

  While WebVTT regions enable us to satisfy all of the above points, the specification isn’t actually complete yet and some of the above needs aren’t satisfied yet.

  We have an open bug to move a region elsewhere. A first discussion at FOMS seemed to to indicate that we’ll have to add syntax for updating a region at a particular time and thus give region definitions a way to be valid only for a certain time frame. I can imagine that the region definitions that we have in the header of the WebVTT file now would have an implicitly defined time frame from the start to the end of the file, but can be overruled by a re-definition anywhere within the WebVTT file. That redefinition needs to provide a start and end time.

  We registered a bug to add specifying the width and height of regions (and possibly of cues) by em (i.e. by multiples of the largest character in a font). This should allow us to have the region grow/shrink around the region anchor point with a change of font size by script or a user. em specifications should also be applied to cues – that matches the column count of CEA708/608 better.

  When regions overlap, the original region extension spec already suggested a “layer” cue setting. It will be easy to add it.

  Another change that we will ultimately need is the “scroll” setting : we will need to introduce support for scrolling text down or from left-to-right or right-to-left, e.g. vertical scrolling text seems to be used in some Chinese caption use cases.

  2. Unify Rendering Approach

  The introduction of regions created a second code path in the rendering spec with some duplication. At FOMS we discussed if it was possible to unify that. The suggestion is to render all cues into a region. Those that are not part of a region would be rendered into an anonymous region that covers the complete viewport. There may be some consequences to this, e.g. cue settings should be usable across all cues, no matter whether or not part of a region, and avoiding cue overlap may need to be done within regions.

  Here’s a rough outline of the path of the new rendering algorithm :

  (1) Render the regions :

  Specified Region	Anonymous Region
  Render values as given :	Render following values :
  width lines regionanchor viewportanchor scroll	100% videoheight/lineheight 0,0 0,0 none

  (2) Render the cues :

  • Create a cue box and put it in its region (anonymous if none given).
  • Calculate position & size of cue box from cue settings (position, line, size).
  • Calculate position of cue text inside cue box from remaining cue settings (vertical, align).

  3. Vertical Features

  WebVTT includes vertical rendering, both right-to-left and left-to-right. However, regions are not defined for vertical. Eventually, we’re going to have to look at the vertical features of WebVTT with more details and figure out whether the spec is working for them and what real-world requirements we have missed. We hope we can get some help from users in countries where vertically rendered captions/subtitles are the norm.

  4. Best Practices

  Some of he WebVTT users at FOMS suggested it would be advantageous to start a list of “best practices” for how to author captions with WebVTT. Example recommendations are :

  • Use line numbers only to position cues from top or bottom of viewport. Don’t use otherwise.
  • Note that when the user increases the fontsize in rollup captions and thus introduces new line breaks, your cues will roll by faster because the number of lines of a rollup is fixed.
  • Make sure to use &lrm ; and &rlm ; UTF-8 markers to control the directionality of your text.

  It would be nice if somebody started such a document.

  5. Non-caption use cases

  Instead of continuing to look back and improve our support of captions/subtitles in WebVTT, one session at FOMS also went ahead and looked forward to other use cases. The following requirements came out of this :

  5.1 Preview Thumbnails

  A common use case for timed data is the use of preview thumbnails on the navigation bar of videos. A native implementation of preview thumbnails would allow crawlers and search engines to have a standardised way of extracting timed images for media files, so introduction of a new @kind value “thumbnails” was suggested.

  The content of a “thumbnails” cue could be any of :

  • an image URL
  • a sprite URL to a single image
  • a spatial & temporal media fragment URL to a media resource
  • base64 encoded image (data URI)
  • an iframe offset to the media resource

  The suggestion is to allow anything that would work in a img @src attribute as value in a cue of @kind=”thumbnails”. Responsive images might also be useful for a track of @kind=”thumbnails”. It may even be possible to define an inband thumbnail track based on the track of @kind=”thumbnails”. Such cues should also work in the JavaScript track API.

  5.2 Chapter markers

  There is interest to put richer content than just a chapter title into chapter cues. Often, chapters consist of a title, text and and image. The text is not so important, but the image is used almost everywhere that chapters are used. There may be a need to extend chapter cue content with images, similar to what a @kind=”thumbnails” track offers.

  The conclusion that we arrived at was that we need to make @kind=”thumbnails” work first and then look at using the learnings from that to extend @kind=”chapters”.

  5.3 Inband tracks for live video

  A difficult topic was opened with the question of how to transport text tracks in live video. In live captioning, end times are never created for cues, but are implied by the start time of the next cue. This is a use case that hasn’t been addressed in HTML5/WebVTT yet. An old proposal to allow a special end time value of “NEXT” was discussed and recommended for adoption. Also, there was support for the spec change that stops blocking loading VTT until all cues have been loaded.

  5.4 Cross-domain VTT loading

  A brief discussion centered around the fact that the spec disallows cross-domain loading of WebVTT files, but that no browser implements this. This needs to be discussion at the HTML WG level.

  6. Regions in live captioning

  The final topic that we discussed was how we could provide support for regions in live captioning.

  • The currently active region definitions will need to be come part of every header of every VTT file segment that HLS uses, so it’s available in case the cues in the segment file reference it.
  • “NEXT” in end time markers would make authoring of live captioned VTT files easier.
  • If the application wants to use 1 word at a time and doesn’t want to delay sending the word until the full cue is authored (e.g. in a Hangout type environment), we will need to introduce the concept of “cue continuation markers”, so we know that a cue could be extended with the next VTT file fragment.

  This is an extensive and impressive amount of discussion around WebVTT and a lot of new work to be performed in the future. I’m very grateful for all the people who have contributed to these discussions at FOMS and will hopefully continue to help get the specifications right.

• How to Check Website Traffic As Accurately As Possible

  18 août 2023, par Erin — Analytics Tips

  If you want to learn about the health of your website and the success of your digital marketing initiatives, there are few better ways than checking your website traffic. 

  It’s a great way to get a quick dopamine hit when things are up, but you can also use traffic levels to identify issues, learn more about your users or benchmark your performance. That means you need a reliable and easy way to check your website traffic over time — as well as a way to check out your competitors’ traffic levels, too. 

  In this article, we’ll show you how to do just that. You’ll learn how to check website traffic for both your and your competitor’s sites and discover why some methods of checking website traffic are better than others. 

  Why check website traffic ? 

  Dopamine hits aside, it’s important to constantly monitor your website’s traffic for several reasons.

  

  Benchmark site performance

  Keeping regular tabs on your traffic levels is a great way to track your website’s performance over time. It can help you plan for the future or identify problems. 

  For instance, growing traffic levels may mean expanding your business’s offering or investing in more inventory. On the flip side, decreasing traffic levels may suggest it’s time to revamp your marketing strategies or look into issues impacting your SEO. 

  Analyse user behaviour

  Checking website traffic and user behaviour lets marketing managers understand how users interact with your website. Which pages are they visiting ? Which CTAs do they click on ? What can you do to encourage users to take the actions you want ? You can also identify issues that lead to high bounce rates and other problems. 

  The better you understand user behaviour, the easier it will be to give them what they want. For example, you may find that users spend more time on your landing pages than they do your blog pages. You could use that information to revise how you create blog posts or focus on creating more landing pages. 

  Improve the user experience

  Once you understand how users behave on your website, you can use that information to fix errors, update your content and improve the user experience for the site. 

  You can even personalise the experience for customers, leading to significant growth. Research shows companies that grow faster derive 40% more of their revenue from personalisation. 

  That could come in the form of sweeping personalisations — like rearranging your website’s navigation bar based on user behaviour — or individual personalisation that uses analytics to transform sections or entire pages of your site based on user behaviour. 

  Optimise marketing strategies

  You can use website traffic reports to understand where users are coming from and optimise your marketing plan accordingly. You may want to double down on organic traffic, for instance, or invest more in PPC advertising. Knowing current traffic estimates and how these traffic levels have trended over time can help you benchmark your campaigns and prioritise your efforts. 

  Increasing traffic levels from other countries can also help you identify new marketing opportunities. If you start seeing significant traffic levels from a neighbouring country or a large market, it could be time to take your business international and launch a cross-border campaign. 

  Filter unwanted traffic

  A not-insignificant portion of your site’s traffic may be coming from bots and other unwanted sources. These can compromise the quality of your analytics and make it harder to draw insights. You may not be able to get rid of this traffic, but you can use analytics tools to remove it from your stats. 

  How to check website traffic on Matomo

  If you want to check your website’s traffic, you’d be forgiven for heading to Google Analytics first. It’s the most popular analytics tool on the market, after all. But if you want a more reliable assessment of your website’s traffic, then we recommend using Matomo alongside Google Analytics. 

  The Matomo web analytics platform is an open-source solution that helps you collect accurate data about your website’s traffic and make more informed decisions as a result — all while enhancing the customer experience and ensuring GDPR compliance and user privacy. 

  Matomo also offers multiple ways to check website traffic :

  • Visits log report
  • Real-time visitor map
  • Visits in real-time report

  Let’s look at all of them one by one. 

  The visits log report is a unique rundown of all of the individual visitors to your site. This offers a much more granular view than other tools that just show the total number of visitors for a given period. 

  

  You can access the visits log report by clicking on the reporting menu, then clicking Visitor and Visits Log. From there, you’ll be able to scroll through every user session and see the following information :

  • The location of the user
  • The total number of actions they took
  • The length of time on site
  • How they arrived at your site
  • And the device they used to access your site 

  This may be overwhelming if your site receives thousands of visitors at a time. But it’s a great way to understand users at an individual level and appreciate the lifetime activity of specific users. 

  The Real-time visitor map is a visual display of users’ location for a given timeframe. If you have an international website, it’s a fantastic way to see exactly where in the world your traffic comes from.

  

  You can access the Real-time Visitor Map by clicking Visitor in the main navigation menu and then Real-time Map. The map itself is colour-coded. Larger orange bubbles represent recent visits, and smaller dark orange and grey bubbles represent older visits. The map will refresh every five seconds, and new users appear with a flashing effect. 

  If you run TV or radio adverts, Matomo’s Real-time Map provides an immediate read on the effectiveness of your campaign. If your map lights up in the minutes following your ad, you know it’s been effective. It can also help you identify the source of bot attacks, too. 

  Finally, the Visits in Real-time report provides a snapshot of who is browsing your website. You can access this report under Visitors > Real-time and add it to your custom dashboards as a widget. 

  Open the report, and you’ll see the real-time flow of your site’s users and counters for visits and pageviews over the last 30 minutes and 24 hours. The report refreshes every five seconds with new users added to the top of the report with a fade-in effect.

  

  The report provides a snapshot of each visitor, including :

  • Whether they are new or a returning 
  • Their country
  • Their browser
  • Their operating system
  • The number of actions they took
  • The time they spent on the site
  • The channel they came in from
  • Whether the visitor converted a goal

  3 other ways to check website traffic

  You don’t need to use Matomo to check your website traffic. Here are three other tools you can use instead. 

  How to check website traffic on Google Analytics

  Google Analytics is usually the first starting point for anyone looking to check their website traffic. It’s free to use, incredibly popular and offers a wide range of traffic reports. 

  Google Analytics lets you break down historical traffic data almost any way you wish. You can split traffic by acquisition channel (organic, social media, direct, etc.) by country, device or demographic.

  

  It also provides real-time traffic reports that give you a snapshot of users on your site right now and over the last 30 minutes. 

  

  Google Analytics may be one of the most popular ways to check website traffic, but it could be better. Google Analytics 4 is difficult to use compared to its predecessor, and it also limits the amount of data you can track in accordance with privacy laws. If users refuse your cookie consent, Google Analytics won’t record these visits. In other words, you aren’t getting a complete view of your traffic by using Google Analytics alone. 

  That’s why it’s important to use Google Analytics alongside other web analytics tools (like Matomo) that don’t suffer from the same privacy issues. That way, you can make sure you track every single user who visits your site. 

  How to check website traffic on Google Search Console

  Google Search Console is a free tool from Google that lets you analyse the search traffic that your site gets from Google. 

  The top-line report shows you how many times your website has appeared in Google Search, how many clicks it has received, the average clickthrough rate and the average position of your website in the search results. 

  

  Google Search Console is a great way to understand what you rank for and how much traffic your organic rankings generate. It will also show you which pages are indexed in Google and whether there are any crawling errors. 

  Unfortunately, Google Search Console is limited if you want to get a complete view of your traffic. While you can analyse search traffic in a huge amount of detail, it will not tell you how users who access your website directly or via social media behave. 

  How to check website traffic on Similarweb

  Similarweb is a website analysis tool that estimates the total traffic of any site on the internet. It is one of the best tools for estimating how much traffic your competitors receive. 

  What’s great about Similarweb is that it estimates total traffic, not just traffic from search engines like many SEO tools. It even breaks down traffic by different channels, allowing you to see how your website compares against your competitors. 

  

  As you can see from the image above, Similarweb provides an estimate of total visits, bounce rate, the average number of pages users view per visit and the average duration on the site. The company also has a free browser extension that lets you check website traffic estimates as you browse the web. 

  You can use Similarweb for free to a point. But to really get the most out of this tool, you’ll need to upgrade to a premium plan which starts at $125 per user per month. 

  The price isn’t the only downside of using Similarweb to check the traffic of your own and your competitor’s websites. Ultimately, Similarweb is only an estimate — even if it’s a reasonably accurate one — and it’s no match for a comprehensive analytics tool. 

  7 website traffic metrics to track

  Now that you know how to check your website’s traffic, you can start to analyse it. You can use plenty of metrics to assess the quality of your website traffic, but here are some of the most important metrics to track. 

  • New visitors : These are users who have never visited your website before. They are a great sign that your marketing efforts are working and your site is reaching more people. But it’s also important to track how they behave on the website to ensure your site caters effectively to new visitors. 
  • Returning visitors : Returning visitors are coming back to your site for a reason : either they like the content you’re creating or they want to make a purchase. Both instances are great. The more returning visitors, the better. 
  • Bounce rate : This is a measure of how many users leave your website without taking action. Different analytics tools measure this metric differently.
  • Session duration : This is the length of time users spend on your website, and it can be a great gauge of whether they find your site engaging. Especially when combined with the metric below. 
  • Pages per session : This measures how many different pages users visit on average. The more pages they visit and the longer users spend on your website, the more engaging it is. 
  • Traffic source : Traffic can come from a variety of sources (organic, direct, social media, referral, etc.) Tracking which sources generate the most traffic can help you analyse and prioritise your marketing efforts. 
  • User demographics : This broad metric tells you more about who the users are that visit your website, what device they use, what country they come from, etc. While the bulk of your website traffic will come from the countries you target, an influx of new users from other countries can open the door to new opportunities.

  Why do my traffic reports differ ?

  If you use more than one of the methods above to check your website traffic, you’ll quickly realise that every traffic report differs. In some cases, the reasons are obvious. Any tool that estimates your traffic without adding code to your website is just that : an estimate. Tools like Similarweb will never offer the accuracy of analytics platforms like Matomo and Google Analytics. 

  But what about the differences between these analytics platforms themselves ? While each platform has a different way of recording user behaviour, significant differences in website traffic reports between analytics platforms are usually a result of how each platform handles user privacy. 

  A platform like Google Analytics requires users to accept a cookie consent banner to track them. If they accept, great. Google collects all of the data that any other analytics platform does. It may even collect more. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports. 

  That doesn’t happen with all analytics platforms, however. A privacy-focused alternative like Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen from Google Analytics. This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not. And it’s why traffic reports in Matomo are often much higher than they are in Google Analytics.

  

  Given that around half (47.32%) of adults in the European Union refuse to allow the use of personal data tracking for advertising purposes and that 95% of people will reject additional cookies when it is easy to do so, this means you could have vastly different traffic reports — and be missing out on a significant amount of user data. 

  If you’re serious about using web analytics to improve your website and optimise your marketing campaigns, then it is essential to use another analytics platform alongside Google Analytics. 

  Get more accurate traffic reports with Matomo

  There are several methods to check website traffic. Some, like Similarweb, can provide estimates on your competitors’ traffic levels. Others, like Google Analytics, are free. But data doesn’t lie. Only privacy-focused analytics solutions like Matomo can provide accurate reports that account for every visitor. 

  Join over one million organisations using Matomo to accurately check their website traffic. Try it for free alongside GA today. No credit card required. 

• Inside WebM Technology : VP8 Intra and Inter Prediction

  20 juillet 2010, par noreply@blogger.com (Lou Quillio)
  Continuing our series on WebM technology, I will discuss the use of prediction methods in the VP8 video codec, with special attention to the TM_PRED and SPLITMV modes, which are unique to VP8.

  
  

  First, some background. To encode a video frame, block-based codecs such as VP8 first divide the frame into smaller segments called macroblocks. Within each macroblock, the encoder can predict redundant motion and color information based on previously processed blocks. The redundant data can be subtracted from the block, resulting in more efficient compression.

  
  Image by Fido Factor, licensed under Creative Commons Attribution License.
  Based on a work at www.flickr.com

  
  

  A VP8 encoder uses two classes of prediction :

  • Intra prediction uses data within a single video frame
  • Inter prediction uses data from previously encoded frames

  The residual signal data is then encoded using other techniques, such as transform coding.

  
  

  VP8 Intra Prediction Modes

  VP8 intra prediction modes are used with three types of macroblocks :

  • 4x4 luma
  • 16x16 luma
  • 8x8 chroma

  Four common intra prediction modes are shared by these macroblocks :
  

  • H_PRED (horizontal prediction). Fills each column of the block with a copy of the left column, L.
  • V_PRED (vertical prediction). Fills each row of the block with a copy of the above row, A.
  • DC_PRED (DC prediction). Fills the block with a single value using the average of the pixels in the row above A and the column to the left of L.
  • TM_PRED (TrueMotion prediction). A mode that gets its name from a compression technique developed by On2 Technologies. In addition to the row A and column L, TM_PRED uses the pixel P above and to the left of the block. Horizontal differences between pixels in A (starting from P) are propagated using the pixels from L to start each row.

  For 4x4 luma blocks, there are six additional intra modes similar to V_PRED and H_PRED, but correspond to predicting pixels in different directions. These modes are outside the scope of this post, but if you want to learn more see the VP8 Bitstream Guide.

  
  

  As mentioned above, the TM_PRED mode is unique to VP8. The following figure uses an example 4x4 block of pixels to illustrate how the TM_PRED mode works :

  

  Where C, As and Ls represent reconstructed pixel values from previously coded blocks, and X₀₀ through X₃₃ represent predicted values for the current block. TM_PRED uses the following equation to calculate X_ij :

  
  

  X_ij = L_i + A_j - C (i, j=0, 1, 2, 3)

  
  

  Although the above example uses a 4x4 block, the TM_PRED mode for 8x8 and 16x16 blocks works in the same fashion.

  TM_PRED is one of the more frequently used intra prediction modes in VP8, and for common video sequences it is typically used by 20% to 45% of all blocks that are intra coded. Overall, together with other intra prediction modes, TM_PRED helps VP8 to achieve very good compression efficiency, especially for key frames, which can only use intra modes (key frames by their very nature cannot refer to previously encoded frames).

  
  

  VP8 Inter Prediction Modes

  
  

  In VP8, inter prediction modes are used only on inter frames (non-key frames). For any VP8 inter frame, there are typically three previously coded reference frames that can be used for prediction. A typical inter prediction block is constructed using a motion vector to copy a block from one of the three frames. The motion vector points to the location of a pixel block to be copied. In most video compression schemes, a good portion of the bits are spent on encoding motion vectors ; the portion can be especially large for video encoded at lower datarates.

  
  

  Like previous VPx codecs, VP8 encodes motion vectors very efficiently by reusing vectors from neighboring macroblocks (a macroblock includes one 16x16 luma block and two 8x8 chroma blocks). VP8 uses a similar strategy in the overall design of inter prediction modes. For example, the prediction modes "NEAREST" and "NEAR" make use of last and second-to-last, non-zero motion vectors from neighboring macroblocks. These inter prediction modes can be used in combination with any of the three different reference frames.

  
  

  In addition, VP8 has a very sophisticated, flexible inter prediction mode called SPLITMV. This mode was designed to enable flexible partitioning of a macroblock into sub-blocks to achieve better inter prediction. SPLITMV is very useful when objects within a macroblock have different motion characteristics. Within a macroblock coded using SPLITMV mode, each sub-block can have its own motion vector. Similar to the strategy of reusing motion vectors at the macroblock level, a sub-block can also use motion vectors from neighboring sub-blocks above or left to the current block. This strategy is very flexible and can effectively encode any shape of sub-macroblock partitioning, and does so efficiently. Here is an example of a macroblock with 16x16 luma pixels that is partitioned to 16 4x4 blocks :

  
  

  

  
  

  where New represents a 4x4 bock coded with a new motion vector, and Left and Above represent a 4x4 block coded using the motion vector from the left and above, respectively. This example effectively partitions the 16x16 macroblock into 3 different segments with 3 different motion vectors (represented below by 1, 2 and 3) :

  
  

  

  
  

  Through effective use of intra and inter prediction modes, WebM encoder implementations can achieve great compression quality on a wide range of source material. If you want to delve further into VP8 prediction modes, read the VP8 Bitstream Guide or examine the reconintra.c and rdopt.c files in the VP8 source tree.

  
  

  Yaowu Xu, Ph.D. is a codec engineer at Google.