Glossary
Per-Title Encoding

Per-Title Encoding

Roei Hazout

When it comes to online video streaming, ensuring that viewers get the best possible experience can be tricky. Everyone's internet connection is different, from blazing-fast fiber to more sluggish mobile networks. And the way videos are encoded — the process of compressing videos to make them streamable — plays a huge role in how smooth or choppy your viewing experience is. 

That's why per-title encoding is necessary. It's a game-changer in online video encoding, designed to optimize the video quality for each individual title. But how exactly does it work? And why is it important for streaming platforms? Let’s break it down.

What is Per-Title Encoding?

In simple terms, per-title encoding refers to customizing the encoding process for each video or "title" in a content library, instead of applying a one-size-fits-all approach. Traditional encoding uses fixed bitrates or quality settings across all videos, regardless of the video's characteristics. 

However, not all videos are created equal—some are fast-paced, while others are slow-moving or heavily animated. With per-title encoding, the encoding parameters are adapted based on the unique attributes of each video, resulting in more efficient compression and better viewing experiences.

Think of it like tailoring a suit: rather than using the same measurements for everyone, per-title encoding adjusts the "fit" for each video. This means that a movie with lots of visual effects or action scenes might get more bitrate to preserve quality, while a simple talk-show episode might need less.

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How Netflix Introduced Per-Title Encoding

Netflix pioneered per-title encoding in 2015 to optimize video quality and reduce bandwidth usage. Instead of using a fixed bitrate for all videos, Netflix analyzes each title’s complexity and assigns a unique encoding profile.

Simple videos get lower bitrates, saving bandwidth, while complex content receives higher bitrates to maintain quality. This shift led to bandwidth savings without compromising video quality, enhancing user experience across devices and connection speeds​. 

Netflix’s innovation has since become a standard across major streaming platforms. Improving the streaming ecosystem with advanced technologies like per-title encoding, and CDNs. 

How Per-Title Encoding Works

Now that you have a general idea of what per-title encoding is, let’s talk about how it works.

  1. Analysis: The first step in the process involves analyzing the video. Specialized algorithms examine various factors like motion, color complexity, scene transitions, and overall visual detail. Based on this analysis, the system identifies how complex the video is and how much bitrate (data per second) it needs to maintain a good balance between quality and file size.
  2. Custom Encoding Recipe: Once the analysis is done, a custom encoding “recipe” is created for that specific video. This recipe determines how the video will be encoded at different resolutions (e.g., 720p, 1080p, 4K) and bitrates, ensuring that it looks great on all types of devices, from smartphones to big-screen TVs.
  3. Multiple Encodes: The video is then encoded at multiple bitrates and resolutions according to the custom recipe. This allows the streaming service to deliver the best quality video depending on the user’s internet connection. If a user has a slower connection, the platform will serve them a lower-resolution version of the video, but still optimized for that specific title.
  4. Adaptive Bitrate Streaming: With these different versions available, per-title encoding works hand-in-hand with adaptive bitrate streaming, which dynamically adjusts the video quality based on the viewer's bandwidth. So, no matter the strength of your connection, you get the best possible video quality.

Technicalities of Per-Title Encoding

To dive deeper into how this method works, let's break down the key technical components and processes involved in optimizing video content.

1. Content Complexity Analysis

At the core of the process is the ability to analyze a video’s complexity. The system evaluates various factors, including:

  • Motion Vector Analysis: High-motion scenes, such as action sequences, require more data to preserve clarity. In contrast, static scenes can be encoded with less data.
  • Spatial Complexity: Detailed textures or gradients in a scene demand more bitrate to avoid compression artifacts.
  • Temporal Complexity: Rapid scene transitions or high frame rates require careful bitrate allocation to ensure smooth playback.

These evaluations help dynamically calculate the ideal encoding settings for each video.

2. Bitrate Ladder Optimization

Instead of using a fixed bitrate ladder, a custom bitrate ladder is created for each video based on its complexity. This ensures that simpler content can use lower bitrates without sacrificing quality, while more complex videos are encoded with higher bitrates to maintain clarity. 

The goal is to identify the "convex hull," a curve that represents the optimal trade-off between bitrate and quality, maximizing efficiency.

3. Rate-Distortion Optimization (RDO)

RDO is a critical step that balances compression quality with file size. It evaluates how much distortion (quality loss) is acceptable for each level of compression, ensuring that the video looks its best at each resolution. 

Multiple passes are often performed during encoding to refine this balance and achieve the best results for every frame and scene.

4. Multi-Pass Encoding

Multi-pass encoding is a common practice where the encoder first analyzes the content in a preliminary pass, then uses the collected data to optimize bitrate allocation during the actual encoding pass. 

This ensures high-motion or complex scenes get more bitrate, while simpler scenes get less, leading to better overall quality with smaller file sizes.

5. Dynamic Resolution Switching

In combination with adaptive bitrate streaming (ABR), dynamic resolution switching allows the system to deliver different resolutions of the same video depending on the viewer's internet speed. 

This technique ensures that users with slower connections still get a smooth viewing experience without overloading their network, while those with faster connections can enjoy higher resolutions.

6. Codec Efficiency

This method is highly effective when combined with efficient codecs like H.265/HEVC, VP9, or AV1. These codecs offer better compression, especially for high-definition and 4K content. 

By using such codecs alongside this optimization method, streaming platforms can significantly reduce bandwidth usage without compromising video quality.

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Per-Title Encoding vs. Traditional Encoding

When comparing per-title encoding to traditional encoding methods, the differences are clear, and they highlight why the former is becoming a preferred approach for video streaming platforms.

Aspect Traditional Encoding Per-Title Encoding
Video Analysis No video-specific analysis, uses fixed settings Detailed analysis of each video's content
Bitrate Allocation Same bitrate for all videos, regardless of complexity Custom bitrate based on video complexity
Video Quality Inconsistent; fast-paced videos may lose quality Optimized for each video, maintaining high quality
File Size Larger, sometimes inefficiently sized files Smaller, efficiently sized files
Bandwidth Efficiency Low; can use excessive data or reduce quality High; optimized for both quality and data efficiency
Adaptability to Content Not adaptable; applies the same settings to all videos Highly adaptable; adjusts to each video's unique needs
Performance on Low Bandwidth Prone to buffering and quality drops Better performance with adaptive bitrate streaming
Cost Efficiency Higher costs due to larger file sizes and bandwidth usage Lower costs due to smaller file sizes and efficient usage

Streaming platforms have seen a significant 80% reduction in storage and delivery costs by adopting per-title encoding. This is because per-title encoding focuses on the most effective bitrate ladder, reducing unnecessary data and storage requirements.

Per-Title Encoding with FFMPEG

For developers and engineers looking to implement per-title encoding using FFmpeg, a powerful open-source multimedia framework, the process involves combining FFmpeg’s built-in tools with custom scripting to analyze and encode video content efficiently. 

Here’s how you can achieve per-title encoding with FFmpeg:

No. Step Description Command Example
1 Content Analysis with FFmpeg Use ffprobe to extract metadata and analyze video complexity, including frame rate, resolution, and bitrate. bash ffprobe -v error -show_entries stream=width,height,bit_rate -of default=noprint_wrappers=1 input.mp4
2 Custom Bitrate Ladders Encode videos at multiple resolutions and bitrates based on complexity analysis. This helps optimize bitrate for different types of content (e.g., action vs. static scenes). bash ffmpeg -i input.mp4 -vf scale=-2:720 -b:v 1500k -c:a aac -ar 48000 -b:a 128k output_720p.mp4
bash ffmpeg -i input.mp4 -vf scale=-2:480 -b:v 800k -c:a aac -ar 48000 -b:a 96k output_480p.mp4
3 Two-Pass Encoding First pass gathers video statistics, while the second pass uses this data to optimize bitrate distribution, ensuring high quality and low file sizes. bash ffmpeg -y -i input.mp4 -c:v libx264 -b:v 1500k -pass 1 -an -f null /dev/null && ffmpeg -i input.mp4 -c:v libx264 -b:v 1500k -pass 2 -c:a aac output_720p.mp4
4 Adaptive Bitrate Streaming Create multiple versions of a video at different bitrates and resolutions, then combine them into a single adaptive bitrate playlist (HLS or DASH) for smooth streaming. bash ffmpeg -i input_720p.mp4 -i input_480p.mp4 -map 0 -map 1 -c copy -f hls -hls_time 10 -hls_playlist_type vod master.m3u8
5 Automation with Scripting Use scripting to automate the entire process, from video analysis to encoding, generating multiple resolutions, and packaging for adaptive bitrate streaming. N/A (Customize scripting based on workflow; no specific command provided for scripting)

Benefits of Per-Title Encoding

The benefits of per-title encoding are significant, not only for the viewer but also for streaming platforms.

1. Better Video Quality

Because each video is encoded specifically based on its characteristics, you get better video quality without unnecessarily bloating the file size. 

This ensures that even on slower internet connections, the video looks as good as it can without constant buffering.

2. Reduced File Sizes

Since per-title encoding tailors the bitrate to what is actually needed, it avoids using more data than necessary. 

As a result, file sizes are often smaller than they would be with traditional encoding methods. This helps reduce storage costs for streaming platforms and cuts down on bandwidth consumption for viewers.

3. More Efficient Streaming

For streaming services, this efficiency can lead to fewer buffering issues and a smoother viewing experience overall. 

By using the optimal bitrate for each video, the platform doesn’t have to work as hard to stream the content, leading to a more stable and enjoyable experience for users.

4. Cost Savings for Platforms

Larger files require more storage and bandwidth, which can be costly for streaming platforms. 

Per-title encoding helps keep file sizes in check, reducing the amount of data being streamed and stored, which can result in significant cost savings, especially for large content libraries.

5. Improved Mobile Viewing

Mobile connections can be unpredictable. With per-title encoding, even those on slower networks can enjoy good-quality video without suffering from endless buffering or pixelation. 

This makes mobile video consumption more enjoyable and less frustrating.

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Use Cases for Per-Title Encoding

Per-title encoding isn’t just for big-budget movies or high-action sports broadcasts; it can be used in a variety of online video encoding scenarios:

1. Streaming Platforms

Netflix was one of the pioneers in per-title encoding, and for good reason. With millions of users around the world, the company needed a way to deliver high-quality video at all times, regardless of a viewer's internet connection. 

Other streaming giants like Amazon Prime Video and Disney+ also benefit from this approach, ensuring a seamless experience across different devices and connection speeds.

2. Educational Videos

For platforms like Coursera or Khan Academy, where the content often involves simple lectures, per-title encoding ensures that the video is clear without using excessive bandwidth. 

Since the visuals are typically low-motion, the system doesn't need to allocate high bitrates, which reduces file sizes and loading times.

3. Live Streaming and Events

Live OTT streaming platforms such as Twitch or YouTube Live can also leverage per-title encoding to ensure that the streams remain smooth, even for users with fluctuating internet connections. 

For fast-paced events like sports or gaming, per-title encoding can optimize the video in real-time, adjusting bitrates to maintain quality.

4. Corporate Training and Internal Videos

Companies that use video content for training or internal communications can use per-title encoding to deliver videos that don’t require massive amounts of storage or high-speed connections. 

Whether it's a high-quality instructional video or a basic training clip, the system can optimize the content for efficient viewing.

Conclusion

In essence, per-title encoding is an intelligent and effective way to ensure the best possible video quality for every viewer, regardless of their internet connection. By tailoring the encoding process to each specific title, this method balances the need for high-quality video with the practical limitations of bandwidth and file size. 

Published on:
November 21, 2024
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