AWS Partner TrackIt streamlines the content curation process with AI Video Reviewer

Authored by Brad Winett, President and Partner at TrackIt. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.

As the availability and demand for media content continues to explode, companies that deal with large volumes of media assets face the recurring challenge of filtering content to meet distribution guidelines and requirements. Often, this translates into unreasonable amounts of human labor dedicated to manually identifying and editing questionable content. Too often, this labor uses relatively scarce and costly resources like video editors along with their associated high-power equipment, taking time from true value-added creative tasks.

Estimates show that the average medium to large-sized company in the media and entertainment industry dedicates somewhere between 4-10 hours of editing time per hour of content to the curation process. With ever-increasing volumes of content in production along with the rapidly growing universe of media outlets, the need for a solution that helps companies streamline content curation has never been greater.

TrackIt AI Video Reviewer tool

The TrackIt AI Video Reviewer is an Artificial Intelligence Machine Learning (AI/ML) powered smart review tool that helps companies streamline and automate their content curation processes. It is a web-based solution that non-editorial staff can use to search for and mark specific vocabulary and imagery in video assets. The AI Video Reviewer is an ideal solution for companies that handle large volumes of video content that require scrupulous editing to adhere to distribution requirements.

How the tool works

The AI Video Reviewer is a web-based application that runs from any web browser, at any location, freeing the curation effort from any specific geographic or on-premises locality.

Upon sign-in, a user visits a straightforward asset management interface that provides an upload utility for their videos and a list of content available for review.

Support for built-in customization for transcribed word identification is available, and the tool is extensible to recognize other imagery through custom models or more sophisticated AI/ML such as scene detection, sentiment analysis, etc.

After a user selects a video, the AI Video Reviewer presents an easy-to-use video player interface that allows them to quickly identify and mark items of interest for deletion, retention, or with comments for editors to act on. Keyboard shortcuts to jump to marked occurrences on the timeline are available for operator efficiency.

Once a video review is complete, users have the choice to export Marker/Edit Decision Lists  that video editors can use to make final cuts and edits.

AWS Services

The following services from Amazon Web Services (AWS) are used in the AI Video Reviewer:

• Amazon Rekognition: Analyzes video from the ingested content for segment detection (to detect technical cues and shots) and content moderation (to detect graphic or questionable content).
• Amazon Transcribe: Analyzes audio from ingested content. This helps create a transcript file from the audio to identify and filter unwanted words.
• AWS Amplify Video: Provides end users with a playback video on the web-based UI. An HLS playlist is created using Amplify Video.
• AWS Elemental MediaConvert: A file-based video transcoding service with broadcast-grade features. MediaConvert allows you to easily create video-on-demand (VOD) content for broadcast and multiscreen delivery at scale.
• Amazon CloudFront: This content delivery network (CDN) is used to deliver website content and data.
• Amazon Cognito: Provides user authentication and enables user sign-up, sign-in, and access control to web and mobile apps.
• Amazon Dynamo DB: Stores results of AI/ML jobs. Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-region replication, in-memory caching, and data export tools.
• AWS Lambda: Hosts code that processes metadata coming from API requests, CloudWatch Events, or SNS Topics.
• Amazon CloudWatch: CloudWatch provides you with data and actionable insights to monitor your applications, respond to system-wide performance changes, and optimize resource utilization.
• Amazon SQS: Message queuing service used to process job results from Rekognition and Transcribe when a job starts, completes, or fails. (AWS Lambda is used to process messages. Amazon SNS or Amazon CloudWatch events send their messages to the SQS Queue).
• Amazon SNS: Sends email notifications to end users and sends job results from Rekognition/MediaConvert/Transcribe to the SQS Queue.
• Amazon AppSync: Serves as the GraphQL API to handle user requests and internal requests to save, fetch, and delete metadata and also generate specific assets.
• Amazon Simple Storage Services (AmazonS3): Ingests video content and stores generated assets (EDL, transcripts, Marker files, HLS playlist).

Conclusion

Companies that handle sizable volumes of content often dedicate excessive amounts of resources to filter questionable content from video assets. Using the AI Video Reviewer lets companies of all sizes realize significant time and cost savings by streamlining and automating their content curation processes.

About TrackIt

TrackIt is a cloud management, consulting and software development solutions company based in Marina del Rey, CA. TrackIt specializes in Cloud-Native, Modern Software Development; DevOps, Infrastructure-As-Code, serverless, CI/CD and containerization with special expertise in media and entertainment workflows, High-Performance Computing environments and data storage.