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  • Les formats acceptés

    28 janvier 2010, par

    Les commandes suivantes permettent d’avoir des informations sur les formats et codecs gérés par l’installation local de ffmpeg :
    ffmpeg -codecs ffmpeg -formats
    Les format videos acceptés en entrée
    Cette liste est non exhaustive, elle met en exergue les principaux formats utilisés : h264 : H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10 m4v : raw MPEG-4 video format flv : Flash Video (FLV) / Sorenson Spark / Sorenson H.263 Theora wmv :
    Les formats vidéos de sortie possibles
    Dans un premier temps on (...)

  • Supporting all media types

    13 avril 2011, par

    Unlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)

  • Création définitive du canal

    12 mars 2010, par

    Lorsque votre demande est validée, vous pouvez alors procéder à la création proprement dite du canal. Chaque canal est un site à part entière placé sous votre responsabilité. Les administrateurs de la plateforme n’y ont aucun accès.
    A la validation, vous recevez un email vous invitant donc à créer votre canal.
    Pour ce faire il vous suffit de vous rendre à son adresse, dans notre exemple "http://votre_sous_domaine.mediaspip.net".
    A ce moment là un mot de passe vous est demandé, il vous suffit d’y (...)

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  • The problems with wavelets

    27 février 2010, par Dark Shikari — DCT, Dirac, Snow, psychovisual optimizations, wavelets

    I have periodically noted in this blog and elsewhere various problems with wavelet compression, but many readers have requested that I write a more detailed post about it, so here it is.

    Wavelets have been researched for quite some time as a replacement for the standard discrete cosine transform used in most modern video compression. Their methodology is basically opposite : each coefficient in a DCT represents a constant pattern applied to the whole block, while each coefficient in a wavelet transform represents a single, localized pattern applied to a section of the block. Accordingly, wavelet transforms are usually very large with the intention of taking advantage of large-scale redundancy in an image. DCTs are usually quite small and are intended to cover areas of roughly uniform patterns and complexity.

    Both are complete transforms, offering equally accurate frequency-domain representations of pixel data. I won’t go into the mathematical details of each here ; the real question is whether one offers better compression opportunities for real-world video.

    DCT transforms, though it isn’t mathematically required, are usually found as block transforms, handling a single sharp-edged block of data. Accordingly, they usually need a deblocking filter to smooth the edges between DCT blocks. Wavelet transforms typically overlap, avoiding such a need. But because wavelets don’t cover a sharp-edged block of data, they don’t compress well when the predicted data is in the form of blocks.

    Thus motion compensation is usually performed as overlapped-block motion compensation (OBMC), in which every pixel is calculated by performing the motion compensation of a number of blocks and averaging the result based on the distance of those blocks from the current pixel. Another option, which can be combined with OBMC, is “mesh MC“, where every pixel gets its own motion vector, which is a weighted average of the closest nearby motion vectors. The end result of either is the elimination of sharp edges between blocks and better prediction, at the cost of greatly increased CPU requirements. For an overlap factor of 2, it’s 4 times the amount of motion compensation, plus the averaging step. With mesh MC, it’s even worse, with SIMD optimizations becoming nearly impossible.

    At this point, it would seem wavelets would have pretty big advantages : when used with OBMC, they have better inter prediction, eliminate the need for deblocking, and take advantage of larger-scale correlations. Why then hasn’t everyone switched over to wavelets then ? Dirac and Snow offer modern implementations. Yet despite decades of research, wavelets have consistently disappointed for image and video compression. It turns out there are a lot of serious practical issues with wavelets, many of which are open problems.

    1. No known method exists for efficient intra coding. H.264′s spatial intra prediction is extraordinarily powerful, but relies on knowing the exact decoded pixels to the top and left of the current block. Since there is no such boundary in overlapped-wavelet coding, such prediction is impossible. Newer intra prediction methods, such as markov-chain intra prediction, also seem to require an H.264-like situation with exactly-known neighboring pixels. Intra coding in wavelets is in the same state that DCT intra coding was in 20 years ago : the best known method was to simply transform the block with no prediction at all besides DC. NB : as described by Pengvado in the comments, the switching between inter and intra coding is potentially even more costly than the inefficient intra coding.

    2. Mixing partition sizes has serious practical problems. Because the overlap between two motion partitions depends on the partitions’ size, mixing block sizes becomes quite difficult to define. While in H.264 an smaller partition always gives equal or better compression than a larger one when one ignores the extra overhead, it is actually possible for a larger partition to win when using OBMC due to the larger overlap. All of this makes both the problem of defining the result of mixed block sizes and making decisions about them very difficult.

    Both Snow and Dirac offer variable block size, but the overlap amount is constant ; larger blocks serve only to save bits on motion vectors, not offer better overlap characteristics.

    3. Lack of spatial adaptive quantization. As shown in x264 with VAQ, and correspondingly in HCEnc’s implementation and Theora’s recent implementation, spatial adaptive quantization has staggeringly impressive (before, after) effects on visual quality. Only Dirac seems to have such a feature, and the encoder doesn’t even use it. No other wavelet formats (Snow, JPEG2K, etc) seem to have such a feature. This results in serious blurring problems in areas with subtle texture (as in the comparison below).

    4. Wavelets don’t seem to code visual energy effectively. Remember that a single coefficient in a DCT represents a pattern which applies across an entire block : this makes it very easy to create apparent “detail” with a DCT. Furthermore, the sharp edges of DCT blocks, despite being an apparent weakness, often result in a “fake sharpness” that can actually improve the visual appearance of videos, as was seen with Xvid. Thus wavelet codecs have a tendency to look much blurrier than DCT-based codecs, but since PSNR likes blur, this is often seen as a benefit during video compression research. Some of the consequences of these factors can be seen in this comparison ; somewhat outdated and not general-case, but which very effectively shows the difference in how wavelets handle sharp edges and subtle textures.

    Another problem that periodically crops up is the visual aliasing that tends to be associated with wavelets at lower bitrates. Standard wavelets effectively consist of a recursive function that upscales the coefficients coded by the previous level by a factor of 2 and then adds a new set of coefficients. If the upscaling algorithm is naive — as it often is, for the sake of speed — the result can look quite ugly, as if parts of the image were coded at a lower resolution and then badly scaled up. Of course, it looks like that because they were coded at a lower resolution and then badly scaled up.

    JPEG2000 is a classic example of wavelet failure : despite having more advanced entropy coding, being designed much later than JPEG, being much more computationally intensive, and having much better PSNR, comparisons have consistently shown it to be visually worse than JPEG at sane filesizes. Here’s an example from Wikipedia. By comparison, H.264′s intra coding, when used for still image compression, can beat JPEG by a factor of 2 or more (I’ll make a post on this later). With the various advancements in DCT intra coding since H.264, I suspect that a state-of-the-art DCT compressor could win by an even larger factor.

    Despite the promised benefits of wavelets, a wavelet encoder even close to competitive with x264 has yet to be created. With some tests even showing Dirac losing to Theora in visual comparisons, it’s clear that many problems remain to be solved before wavelets can eliminate the ugliness of block-based transforms once and for all.

  • Introducing Matomo SEO Web Vitals

    13 septembre 2021, par Ben Erskine — About, Analytics Tips, Plugins

    SEO Web Vitals track your critical website performance metrics and are a core element of SEO best practice. 

    Start using Matomo SEO Web Vitals to monitor your website performance, optimise your visitor experience, improve your search result rankings, and see how your site compares to your competitors.

    SEO Web Vitals

    What are SEO Web Vitals ?

    Web Vitals are made up of a number of important metrics, such as your website’s page speed and loading performance, these metrics all play an important role in search engine optimisation. 

    The more technical terms for these metrics are Page Speed Score, First Contentful Paint (FCP), Final Input Delay (FID), Last Contentful Paint (LCP) and Cumulative Layout Shift (CLS).

    Why should you use SEO Web Vitals ?

    SEO Web Vitals are being used more and more by search engines such as Google to rank websites so they help ensure a great page experience for users who arrive via links from their search results. 

    By monitoring your SEO Web Vitals you can see how good or bad a single page performs and then prioritise the optimisation of strategically important pages to help improve the ranking position within search engine results.

    For ease of use you can receive regular reports in your email inbox and you can configure custom alerts to automatically notify you when a page score changes significantly. This saves time by not having to check page performance scores manually while ensuring you will be notified should there be any important change that needs to be actioned.

    You should use SEO Web Vitals to understand how your site performance is impacting your overall visitor experience.

    Four key benefits of using SEO Web Vitals :

    Improve your search result rankings

    • SEO Web Vitals are a core element of SEO best practice and directly impact your search rankings.
    • Pages that load quickly and are more stable deliver a better user experience, so they’re ranked higher by search engines.

    Optimise your website visitor experience

    • Know how quickly pages on your website load to ensure you deliver an optimal visitor experience.
    • Identify page stability issues and implement the changes needed to enhance your visitor experience.

    Automate your website performance monitoring

    • Have peace of mind knowing if your metrics decrease, you can find and fix the root cause quickly.
    • Configure performance alerts and get automated reports sent to you.

    Incorporate website performance into your competitor analysis

    • These performance metrics are essentially open for anyone to inspect, so you can measure and benchmark your site against competitors. 

    How can I improve my SEO Web Vitals ?

    There are so many ways to improve these performance metrics, here are five of the common contributing factors.

    1. Your page speed score is a weighted average of your other performance metrics, so focus on improving the underlying metrics that contribute to this score.
    2. Ensure you use a high quality web host with an appropriate plan for your level of traffic to help improve your FCP time.
    3. Try removing large elements that aren’t required on your page to improve your LCP time.
    4. Optimise against Total Blocking Time to Improve your FID score.
    5. Consider using a Layout Shift Debugger to improve Your CLS Score

    Guide to Matomo SEO Web Vitals

    For more information and to learn how to configure SEO Web Vitals in Matomo, check out our full guide to SEO Web Vitals.

    You will learn :

    Need more resources ?

    Matomo Plugin SEO Web Vitals

    Matomo SEO Web Vitals FAQs

  • Use data to develop impactful video content

    28 septembre 2021, par Ben Erskine — Analytics Tips, Plugins

    Creating impactful video content is at the heart of what you do. How you really engage with your audience, change behaviours and influence customers to complete your digital goals. But how do you create truly impactful marketing content ? By testing, trialling, analysing and ultimately tweaking and reacting to data-informed insights that gear your content to your audience (rather than simply producing great content and shooting arrows in the dark).

    Whether you want to know how many plays your video has, finish rates, how your video is consumed over time, how video was consumed on specific days or even which locations users are viewing your video content. Media Analytics will gather all of your video data in one place and provide answers to all of these questions (and much more).

    What is impactful video content ?

    Impactful video content grabs your audience’s attention, keeps their attention and promotes them to take measurable action. Be that time spent on your website, goal completion or brand engagement (including following, commenting or sharing on social). Maybe you’ve developed video content, had some really great results, but not consistently, nor every time and it can be difficult to identify what exactly it is that engages and entices each and every time. And we all want to find where that lovely sweet spot is for your audience.

    Embedded video on your website can be a marketing piece that talks about the benefits of your product. Or can be educational or informative that support the brand and overall impression of the brand. And at the very best entertaining at the same time. 

    84% of people say that they’ve been convinced to buy a product or service by watching a brand’s video. Building trust, knowledge and engagement are simply quicker with video. Viewers interact more, and are engaged longer with video, they are more likely to take in the message and trust what they are seeing through educational, informative or even entertaining video marketing content than solely through reading content on a website. And even better they take action, complete goals on your website and engage with your brand (potentially long term).

    It is not only necessary to have embedded video content on your website, it needs to deliver all the elements of a well functioning website, creating the very best user experience is essential to keeping your viewers engaged. This includes ensuring the video is quick to load, on-brand, expected (in format and tone) and easy to use and/or find. Ensuring that your video content is all of these things can mean that your website users will stick around longer on your website, spend more time exploring (and reading) your website and ultimately complete more of your goals. With a great user experience, your users, in turn, are more likely to come back again to your website and trust your brand. 

    All great reasons to create impactful video content that supports your website and brand ! And to analyse data around this behaviour to repeat (or better) the video content that really hits the mark.

    Let’s talk stats

    In terms of video marketing, there are stats to support that viewers retain 95% of a message when they view it in a video format. The psychology behind this should be fairly obvious. It is easier (and quicker) for humans to consume video and watch someone explain something than it is to read and take action. Simply look at the rise of YouTube for explanatory and instructional video content !

    And how about the 87% of marketers that report a positive ROI on using video in their marketing ? This number has steadily increased since 2015 and matches the increase in video views over the years. This should be enough to demonstrate that video marketing is the way forward, however it needs to be the right type of video to create impact and engagement.

    Do you need more reasons to consider honing and refining your video content for your audience ? And riding this wave of impactful video marketing success ?

    But, how do we do that ?

    So, how do you make content that consistently converts your audience to engaged customers ? The answer is in the numbers. The data. Collecting data on each and every piece of media that is produced and put out into the world. Measuring everything, from where it is viewed, how it is viewed, how much of it is viewed and what is your viewer’s action after the fact.

    While Vimeo and YouTube have their own video analytics they are each to their own, meaning a lot more work for you to combine and analyse your data before forming insights that are useful. 

    Your data is collected by external parties, and is owned and used by these platforms, for their own means. Using Web Analytics from Matomo to collect and collate media data can mean your robust data insights are all in one place. And you own the data, keeping your data private, clean and easy to digest. 

    Once your data is across a single platform, your time can be spent on analysing the data (rather than collating) and discovering those super valuable insights. Additionally, these insights can be collated and reported, in one place, and used to inform future digital and video marketing planning. Working with the data and alongside creative teams to produce video that talks to your audience in an impactful way.

    The more data that is collected the deeper the insights. Saving time and money across a single platform and with data-backed insights to inform decisions that can influence the time (and money) spent producing video content that truly hits the mark with your audience. No more wasted investment and firing into the dark without knowledge. 

    Interrogating the ideal length of your video media means it is more likely to be viewed to the end. Or understanding the play rate on your website of any video. How often is the video played ? And which is played more often ? Constant tweaking and updating of your video content planning can be informed by data-driven human-centric insights. By consistently tracking your media, analysing and forming insights you can build upon past work, and create a fuller picture of who your audience is and how they will engage with future video content. Understanding your media over time can lead to informed decisions that can impact the video content and the level of investment to deliver ROI that means something.

    Wrap Up

    Media Analytics puts you at the heart of video engagement. No more guessing at what your audience wants to see, how long or when. Make every piece of video content have the impact you want (and need) to drive engagement, goal completion and customer conversion. Create a user experience that keeps your users on your website for longer. Delivering on all of those delicious digital marketing goals and speaking the language of key stakeholders throughout the business. Back your digital marketing, with truly impactful content, and above all else deliver to your audience content that keeps them engaged and coming back for more.

    Don’t just take our word for it ! Take a look at what Matomo can offer you with streamlined and insightful Media Analytics, all in one place. And go forth and create impactful content, that matters.

    Next steps :

    Check out our detailed user guide to Media Analytics

    Or, if you have questions, see our helpful Video & Audio Analytics FAQ’s