Book Image

Computer Vision on AWS

By : Lauren Mullennex, Nate Bachmeier, Jay Rao
Book Image

Computer Vision on AWS

By: Lauren Mullennex, Nate Bachmeier, Jay Rao

Overview of this book

Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models. You’ll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that’ll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads. By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.
Table of Contents (21 chapters)
1
Part 1: Introduction to CV on AWS and Amazon Rekognition
5
Part 2: Applying CV to Real-World Use Cases
9
Part 3: CV at the edge
12
Part 4: Building CV Solutions with Amazon SageMaker
15
Part 5: Best Practices for Production-Ready CV Workloads

Describing the user journeys

There are four distinct user journeys for our contactless casino and resort: registering by face, registering by ID card, authenticating the user, and updating the user’s profile.

The first journey requires collecting metadata and registering the customer’s profile. You will need to automate steps for checking image quality, confirming uniqueness, and persisting profile state.

Registering a new user

The first step to registering a new user is to validate that the image meets your requirements. Amazon Rekognition’s DetectFaces APIs provide the building blocks for automating these checks, such as the person looking into the camera.

Next, you’ll need to search the Amazon Rekognition collection and determine whether this is a repeat request or new registration. Using the SearchFacesByImages API handles this complexity for you.

After confirming that the incoming face is unique, the IndexFaces API will securely persist...