Automate Highlights and Replay Videos with AWS

Automate Highlights and Replay Videos with AWS

Table of Contents

1. Introduction: Meet Kyle Huang, a Data Scientist from the Solutions Prototyping Team
2. Media Replay Engine (MRE): A Demo to Generate Engaging Video Content
   • 2.1 What is MRE and How Does It Work?
   • 2.2 Benefits of Using MRE
   • 2.3 Creating a Customized Machine Learning Model and Plugins for MRE
   • 2.4 Using MRE's UI and Profile to Configure Video Segmentation
   • 2.5 Scheduling Events and Triggering Video Processing in MRE
   • 2.6 Optimizing Video Segmentation with Plugins
   • 2.7 Generating Clips and Segmenting Video Features Using MRE
     • 2.7.1 Play Ending Clips
     • 2.7.2 Instant Replays in Slow Motion
     • 2.7.3 Highlighting Corner Kicks and Free Kicks
   • 2.8 Creating Personalized Highlighted Replays with MRE
     • 2.8.1 Choosing Features to Include in Highlights
     • 2.8.2 Point and Pose Features in Highlights
   • 2.9 Conclusion: Try MRE for Engaging Video Content Generation

Media Replay Engine (MRE): A Demo to Generate Engaging Video Content

Let's dive into the world of media replay engine (MRE), a powerful serverless framework that aids in the quick generation of engaging video content. In this demo, presented by Kyle Huang, a talented data scientist from the Solutions Prototyping Team, we will explore the capabilities of MRE and how it leverages automated AI/ML processing to enhance viewership.

2.1 What is MRE and How Does It Work?

MRE is a plugin-based architecture that offers a seamless video content creation experience. With its serverless framework, MRE allows customers to pay only for what they use while ensuring optimized cost and low latency. By processing live videos, MRE can generate personalized highlights or add insertions for a more interactive viewing experience.

2.2 Benefits of Using MRE

Utilizing MRE comes with a range of benefits. Firstly, its serverless nature ensures cost optimization and low latency. Additionally, MRE's plugin-based approach makes it easy to customize and Scale according to specific requirements. By leveraging machine learning models and plugins, MRE can extract video features, segment videos, optimize the segmentation, and perform scene labeling.

2.3 Creating a Customized Machine Learning Model and Plugins for MRE

To harness the full potential of MRE, users have the flexibility to integrate their own machine learning models and plugins. These models can be utilized to extract features from videos, while plugins enable algorithm-based video segmentation based on the machine learning results. MRE provides plugins for feature extraction, segment optimization, and segment labeling, acting as integral ingredients for content generation.

2.4 Using MRE's UI and Profile to Configure Video Segmentation

MRE offers an intuitive user interface (UI) that simplifies the configuration process. Users can register their customized machine learning models and plugins within MRE. These plugins help in segmentation, where scenes can be clarified using the associated scene classification plugin. The classification model, trained through Amazon Recognition Custom Labels, enhances the effectiveness of the sync classification plugin.

2.5 Scheduling Events and Triggering Video Processing in MRE

In MRE, users can schedule events using a specific profile. Events can be live sources or vaults, which can be configured using Amazon Media Live or by running a harvester on EC2 instances. The generated HLS streaming automatically triggers a step function in Parallel to process the video chunks. As a result, MRE generates multiple clips from a single video, capturing various moments and actions.

2.6 Optimizing Video Segmentation with Plugins

MRE provides the ability to optimize video segmentation with plugins. These plugins detect and avoid sudden camera changes or commentator speech interruptions, improving the overall quality of video segmentation. By applying optimization techniques, the generated video segments become more coherent and seamless, enhancing the viewers' experience.

2.7 Generating Clips and Segmenting Video Features Using MRE

One of MRE's key functionalities is generating clips and segmenting video features. Each clip or segment delivers a unique part of the video, allowing for easy identification and categorization. With MRE, users can extract play ending clips, show instant replays in slow motion, or highlight specific actions like corner kicks or free kicks.

2.7.1 Play Ending Clips

MRE's play ending clips help viewers quickly identify significant moments within a video, such as when the ball goes out of bounds. These clips provide a concise summary of the play.

2.7.2 Instant Replays in Slow Motion

With MRE, viewers can enjoy instant replays of key actions in slow motion. This feature enhances the viewing experience by allowing users to closely analyze and appreciate the intricacies of a particular play.

2.7.3 Highlighting Corner Kicks and Free Kicks

MRE allows users to highlight specific actions in a video. For example, corner kicks and free kicks can be featured in a personalized replay, giving viewers easy access to the most exciting moments of the Game.

2.8 Creating Personalized Highlighted Replays with MRE

Building upon the segmented clips, MRE enables users to create personalized highlighted replays. By selecting specific features to include in the highlights, users can curate a custom viewing experience.

2.8.1 Choosing Features to Include in Highlights

MRE offers a range of features that users can select to be included in highlights. By handpicking features like goals, dribbles, or player celebrations, users can create an enhanced and engaging replay tailored to their preferences.

2.8.2 Point and Pose Features in Highlights

One interesting feature offered by MRE is the ability to include point and pose actions in highlights. For instance, when a referee points to indicate a foul on the court, MRE's machine learning model can extract this feature and include it in the highlighted replay.

2.9 Conclusion: Try MRE for Engaging Video Content Generation

In conclusion, media replay engine (MRE) presents a powerful framework for generating engaging video content. From automatically segmenting videos to optimizing the segments using plugins, MRE offers a seamless and efficient solution. By utilizing machine learning models and creating custom plugins, users can personalize their content and create highlights that captivate their audience. Try MRE today and unlock the potential of captivating video playback.

Highlights

• MRE: A serverless framework for generating engaging video content
• Customized machine learning models and plugins in MRE
• Dynamic video segmentation and optimization
• Generating clips and segmenting video features
• Creating personalized highlighted replays
• Try MRE today for captivating video playback

FAQs

Q: Can I use my own machine learning models with MRE?
A: Yes, MRE allows for the integration of customized machine learning models, giving you full control over feature extraction and segmentation.

Q: How does MRE optimize video segmentation?
A: MRE utilizes plugins to optimize video segmentation by detecting sudden camera changes and avoiding commentator speech interruptions.

Q: Can I include specific actions like corner kicks in the highlighted replays?
A: Absolutely! MRE enables users to highlight specific actions, including corner kicks, free kicks, and more, in the personalized replays.

Q: Is MRE suitable for both live streaming and vaulted videos?
A: Yes, MRE supports both live sources and vaults. You can configure them using Amazon Media Live or by running a harvester on EC2 instances.

Q: How can I get started with MRE?
A: You can find MRE, along with more than 30 plugin samples and machine learning training notebooks, on GitHub. Explore the samples and notebooks to train your own machine learning models and leverage the power of MRE for engaging video content generation.

Resources

• Media Replay Engine on GitHub
• Amazon Media Live