Custom Frame Extraction Logic

Within the AWS Lambda function, you would implement custom logic to extract specific frames from the video. This might involve:

1. Video Analysis: Simple analysis to identify changes in scenes or detect high-motion segments that might indicate relevant content. While AWS doesn't provide a direct service for frame extraction based on content, you can use general video processing libraries in your Lambda function for this purpose.
2. Using Open-Source Libraries: Incorporate open-source libraries such as FFmpeg or OpenCV in your Lambda function. These libraries can analyze video files and extract frames based on certain criteria, such as fixed time intervals or keyframe extraction.
3. Temporary Storage: Extracted frames can be temporarily stored in Amazon S3 for further analysis. From there, you can use Amazon Rekognition to analyze these frames for malicious content.

Amazon Rekognition

After extracting and storing the relevant frames in S3, you can use Amazon Rekognition to analyze these images. Rekognition can detect various types of content within images, helping you identify potentially harmful or unwanted material.

Integration and Automation

The entire process from video upload, frame extraction, to analysis with Amazon Rekognition can be automated using AWS services. AWS Step Functions can orchestrate the workflow, managing the sequence of tasks from video processing to data storage and analysis.

This setup allows for scalable and efficient processing of video content, focusing your analysis efforts on frames most likely to contain the content of interest, thereby optimizing processing time and costs associated with using Amazon Rekognition.