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• Why iFrame is a good idea

  15 octobre 2009

  I’ve seen some hilariously uninformed posts about the new Apple iFrame specification. Let me take a minute to explain what it actually is.

  First off, as opposed to what the fellow in the Washington Post writes, it’s not really a new format. iFrame is just a way of using formats that we’ve already know and love. As the name suggests, iFrame is just an i-frame only H.264 specification, using AAC audio. An intraframe version of H.264 eh ? Sounds a lot like AVC-Intra, right ? Exactly. And for exactly the same reasons - edit-ability. Whereas AVC-Intra targets the high end, iFrame targets the low end.

  Even when used in intraframe mode, H.264 has some huge advantage over the older intraframe codecs like DV or DVCProHD. For example, significantly better entropy coding, adaptive quantization, and potentially variable bitrates. There are many others. Essentially, it’s what happens when you take DV and spend another 10 years working on making it better. That’s why Panasonic’s AVC-Intra cameras can do DVCProHD quality video at half (or less) the bitrate.

  Why does iFrame matter for editing ? Anyone who’s tried to edit video from one of the modern H.264 cameras without first transcoding to an intraframe format has experienced the huge CPU demands and sluggish performance. Behind the scenes it’s even worse. Because interframe H.264 can have very long GOPs, displaying any single frame can rely on dozens or even hundreds of other frames. Because of the complexity of H.264, building these frames is very high-cost. And it’s a variable cost. Decoding the first frame in a GOP is relatively trivial, while decoding the middle B-frame can be hugely expensive.

  Programs like iMovie mask that from the user in some cases, but at the expensive of high overhead. But, anyone who’s imported AVC-HD video into Final Cut Pro or iMovie knows that there’s a long "importing" step - behind the scenes, the applications are transcoding your video into an intraframe format, like Apple Intermediate or ProRes. It sort of defeats one of the main purposes of a file-based workflow.

  You’ve also probably noticed the amount of time it takes to export a video in an interframe format. Anyone who’s edited HDV in Final Cut Pro has experienced this. With DV, doing an "export to quicktime" is simply a matter of Final Cut Pro rewriting all of the data to disk - it’s essentially a file copy. With HDV, Final Cut Pro has to do a complete reencode of the whole timeline, to fit everything into the new GOP structure. Not only is this time consuming, but it’s essentially a generation loss.

  iFrame solves these issues by giving you an intraframe codec, with modern efficiency, which can be decoded by any of the H.264 decoders that we already know and love.

  Having this as an optional setting on cameras is a huge step forward for folks interested in editing video. Hopefully some of the manufacturers of AVC-HD cameras will adopt this format as well. I’ll gladly trade a little resolution for instant edit-ability.

• Shaking/trembling in video slideshow generated by frames from an image

  18 mai 2017, par raziel

  I have a PHP program which is used to generate a video slideshow from the series of images. Basically, I just need to smoothly ‘move’ from one image area to the another one according to the specified top/left coordinates and width/height area of the image. In order to do smooth movement, I use easing functions during the coordinates calculations for the each of video frame. I make an jpeg image frame based on these calculations using PHP’s Imagick library, then I combine all the generated frames into a single video using ffmpeg command.

  <?php
  
  const TEMP_FRAMES_DIR = __DIR__;
  
  const VIDEO_WIDTH = 1080;
  
  const VIDEO_HEIGHT = 720;
  
  const FPS = 30;
  
  const MOVEMENT_DURATION_SECONDS = 3;
  
  
  
  const IMAGE_PATH = __DIR__ . '/test_image.png';
  
  
  
  $start_coords = [
  
      'x' => 100,
  
      'y' => 100,
  
      'width'  => 480,
  
      'height' => 270
  
  ];
  
  $end_coords = [
  
      'x' => 400,
  
      'y' => 200,
  
      'width'  => 480,
  
      'height' => 270
  
  ];
  
  
  
  $timeline = make_timeline($start_coords, $end_coords);
  
  render_frames(IMAGE_PATH, $timeline);
  
  render_video_from_frames();
  
  
  
  function make_timeline($start_coords, $end_coords) {
  
      $timeline = [];
  
  
  
      $total_frames = MOVEMENT_DURATION_SECONDS * FPS;
  
  
  
      $x_change      = $end_coords['x']      - $start_coords['y'];
  
      $y_change      = $end_coords['y']      - $start_coords['y'];
  
      $width_change  = $end_coords['width']  - $start_coords['width'];
  
      $height_change = $end_coords['height'] - $start_coords['height'];
  
  
  
      for ($i = 0; $i < $total_frames; $i++) {
  
          $timeline[$i] = [
  
              'x'      => easingOutExpo($i, $start_coords['x'], $x_change, $total_frames),
  
              'y'      => easingOutExpo($i, $start_coords['y'], $y_change, $total_frames),
  
              'width'  => easingOutExpo($i, $start_coords['width'], $width_change, $total_frames),
  
              'height' => easingOutExpo($i, $start_coords['height'], $height_change, $total_frames)
  
          ];
  
      }
  
      return $timeline;
  
  }
  
  
  
  function render_frames($image_path, $timeline) {
  
      $image = new Imagick($image_path);
  
      //remove frames from the previous render
  
      array_map('unlink', glob( TEMP_FRAMES_DIR . "/frame*" ));
  
  
  
      foreach ($timeline as $frame_number => $frame) {
  
          $frame_img = clone $image;
  
          $frame_img->cropImage($frame["width"],$frame["height"], $frame["x"],$frame["y"]);
  
          $frame_img->resizeImage(VIDEO_WIDTH, VIDEO_HEIGHT, imagick::FILTER_LANCZOS, 0.9);
  
          $frame_img->writeImage(TEMP_FRAMES_DIR. "/frame$frame_number.jpg");
  
      }
  
  }
  
  
  
  function render_video_from_frames() {
  
      $fps = FPS;
  
      $frames_dir = TEMP_FRAMES_DIR;
  
      $SEP = DIRECTORY_SEPARATOR;
  
  
  
      $video_file = $frames_dir. $SEP . 'video.mp4';
  
  
  
      if (file_exists($video_file)) unlink($video_file);
  
  
  
      system("ffmpeg -framerate $fps -i $frames_dir{$SEP}frame%01d.jpg $video_file");
  
  }
  
  
  
  function easingOutExpo($t, $b, $c, $d) {
  
      return $c * ( -pow( 2, -10 * $t/$d ) + 1 ) + $b;
  
  }

  The problem is that I have annoying shaking/trembling when I need to move at a low speed (like at the end of easing out expo function).
  Here you can get the test video with the problem, the test image which was used and the PHP script :
  https://drive.google.com/drive/u/1/folders/0B9FOrF6IlWaGeHJCS1h6djhVZ28

  You can see this shaking starting from the middle of the test video ( 1.5 sec).

  How can I avoid shaking in such kind of situations ? Thanks in advance !

• Privacy in Business : What Is It and Why Is It Important ?

  13 juillet 2022, par Erin — Privacy

  Privacy concerns loom large among consumers. Yet, businesses remain reluctant to change the old ways of doing things until they become an operational nuisance. 

  More and more businesses are slowly starting to feel the pressure to incorporate privacy best practices. But what exactly does privacy mean in business ? And why is it important for businesses to protect users’ privacy ? 

  In this blog, we’ll answer all of these questions and more. 

  What is Privacy in Business ?

  In the corporate world, privacy stands for the business decision to use collected consumer data in a safe, secure and compliant way. 

  Companies with a privacy-centred culture : 

  • Get explicit user consent to tracking, opt-ins and data sharing 
  • Collect strictly necessary data in compliance with regulations 
  • Ask for permissions to collect, process and store sensitive data 
  • Provide transparent explanations about data operationalisation and usage 
  • Have mechanisms for data collection opt-outs and data removal requests 
  • Implement security controls for storing collected data and limit access permissions to it 

  In other words : They treat consumers’ data with utmost integrity and security – and provide reassurances of ethical data usage. 

  What Are the Ethical Business Issues Related to Privacy ?

  Consumer data analytics has been around for decades. But digital technologies – ubiquitous connectivity, social media networks, data science and machine learning – increased the magnitude and sophistication of customer profiling.

  Big Tech companies like Google and Facebook, among others, capture millions of data points about users. These include general demographics data like “age” or “gender”, as well as more granular insights such as “income”, “past browsing history” or “recently visited geo-locations”. 

  When combined, such personally identifiable information (PII) can be used to approximate the user’s exact address, frequently purchased goods, political beliefs or past medical conditions. Then such information is shared with third parties such as advertisers. 

  That’s when ethical issues arise. 

  The Cambridge Analytica data scandal is a prime example of consumer data that was unethically exploited. 

  Over the years, Google also faced a series of regulatory issues surrounding consumer privacy breaches :

  • In 2021, a Google Chrome browser update put some 2.6 billion users at risk of “surveillance, manipulation and abuse” by providing third parties with data on device usage. 
  • The same year, Google was taken to court for failing to provide full disclosures on tracking performed in Google Chrome incognito mode. A $5 billion lawsuit is still pending.
  • As of 2022, Google Analytics 4 is considered GDPR non-compliant and was branded “illegal” by several European countries. 

  If you are curious, learn more about Google Analytics privacy issues. 

  The bigger issue ? Big Tech companies make the businesses that use their technologies (unknowingly) complicit in consumer data violations.

  In 2022, the Belgian data regulator found the official IAB Europe framework for user consent gathering in breach of GDPR. The framework was used by all major AdTech platforms to issue pop-ups for user consent to tracking. Now ad platforms must delete all data gathered through these. Biggest advertisers such as Procter & Gamble, Unilever, IBM and Mastercard among others, also received a notice about data removal and a regulatory warning on further repercussions if they fail to comply. 

  Big Tech firms have given brands unprecedented access to granular consumer data. Unrestricted access, however, also opened the door to data abuse and unethical use. 

  Examples of Unethical Data Usage by Businesses 

  • Data hoarding means excessively harvesting all available consumer data because a possibility to do so exists, often using murky consent mechanisms. Yet, 85% of collected Big Data is either dark or redundant, obsolete or trivial (ROT).
  • Invasive personalisation based on sensitive user information (or second-guesses), like a recent US marketing campaign, congratulating women on pregnancy (even if they weren’t expecting). Overall, 75% of consumers find most forms of personalisation somewhat creepy. 22% also said they’d leave for another brand due to creepy experiences.
  • Hyper-targeted advertising campaigns based on data consumers would prefer not to share. A recent investigation found that advertising platforms often assign sensitive labels to users (as part of their ad profiles), indicative of their religion, mental issues, history with abuse and so on. This allows advertisers to target such consumers with dubious ads. 

  Ultimately, excessive data collection, paired with poor data protection in business settings, results in major data breaches and costly damage control. Given that cyber attacks are on the rise, every business is vulnerable. 

  Why Should a Business Be Concerned About Protecting the Privacy of Its Customers ?

  Businesses must prioritise customer privacy because that’s what is expected of them. Globally, 89% of consumers say they care about their privacy. 

  As frequent stories about unethical data usage, excessive tracking and data breaches surface online, even more grow more concerned about protecting their data. Many publicly urge companies to take action. Others curtail their relationships with brands privately. 

  

  On average, 45% of consumers feel uncomfortable about sharing personal data. According to KPMG, 78% of American consumers have fears about the amount of data being collected. 40% of them also don’t trust companies to use their data ethically. Among Europeans, 41% are unwilling to share any personal data with businesses. 

  Because the demand for online privacy is rising, progressive companies now treat privacy as a competitive advantage. 

  For example, the encrypted messaging app Signal gained over 42 million active users in a year because it offers better data security and privacy protection. 

  ProtonMail, a privacy-centred email client, also amassed a 50 million user base in several years thanks to a “fundamentally stronger definition of privacy”.

  The growth of privacy-mindful businesses speaks volumes. And even more good things happen to privacy-mindful businesses : 

  • Higher consumer trust and loyalty 
  • Improved attractiveness to investors
  • Less complex compliance
  • Minimum cybersecurity exposure 
  • Better agility and innovation

  It’s time to start pursuing them ! Learn how to embed privacy and security into your operations.