Question 1

What are the typical latency characteristics for real-time video analysis using Rekognition?

Accepted Answer

For real-time video analysis, Rekognition processes video streams asynchronously. Latency for frame-level analysis can vary based on video resolution, frame rate, and the specific API called (e.g., label detection vs. face search). For streaming video, results are typically available within seconds of processing, but direct real-time (sub-100ms) inference on live feeds usually requires client-side buffering and batching for optimal performance.

Question 2

How is data privacy handled for images and videos uploaded for custom model training?

Accepted Answer

When you upload images or videos for Custom Labels training, AWS stores this data securely within your specified AWS region. AWS does not use your content to train models for other customers or for any other purpose without your explicit consent. You retain ownership of your data, and you can delete datasets and trained models at any time, which removes the associated content from Rekognition storage.

Question 3

Can I export the detected labels or facial metadata directly from the console?

Accepted Answer

While the console provides a visual representation and raw JSON output for individual analysis tasks, it does not offer a bulk export feature for large sets of detected labels or facial metadata. For programmatic export and integration with other systems, you would typically use the Rekognition API to process your media and then capture the JSON responses for storage or further processing.

Question 4

What are the cost implications for using the Custom Labels feature versus pre-trained models?

Accepted Answer

Custom Labels incurs costs for model training hours, storage of training data, and inference units when the custom model is used. Pre-trained models are typically billed per image or video segment processed, based on the specific API call (e.g., 'Detect Labels' or 'Detect Faces'). Custom Labels generally involves higher initial setup and training costs but can be more cost-effective for highly specialized, high-volume inference once deployed, depending on the use case.

Question 5

Are there any regional restrictions on where Rekognition models can be deployed or data processed?

Accepted Answer

Amazon Rekognition is available in multiple AWS regions globally. You can choose the region where your data is processed and where your custom models are trained and deployed. This allows you to meet data residency requirements. However, not all features may be available in every region simultaneously, so it's advisable to check the AWS Region Table for the latest service availability.

Amazon Rekognition Website Full Guide (2026)

Introduction

Key Features

Use Cases

Prototyping Computer Vision Integration

How to Use Amazon Rekognition

Access Rekognition Console

Amazon Rekognition Alternatives

Amazon SageMaker Ground Truth

Microsoft Azure Computer Vision

Nanonets

Mighty AI

About Amazon Rekognition

Official Website

Video Mentions

Amazon Rekognition Status