AWS Rekognition provides powerful services for image and video processing. This course, Developing Applications with AWS Rekognition, will demonstrate how these features can be applied to your applications. First, you will cover topics like biometric access based on facial recognition and detection of unsafe content. Next, you will learn how to implement person tracking in security videos and metadata discovery for social media applications. Finally, you will see how other AWS services, like EC2 and Lambda, can work together with Rekognition to build complete applications. When you're finished with this course, you will be ready to use all of the features of Rekognition for image and video processing.
Course Overview Hi. My name is Alan Jones. This course, Developing Applications with AWS Rekognition, introduces you to one of the hot topics in artificial intelligence today, image analysis. Rekognition, running on Amazon Web Services, or AWS for short, is a suite of powerful tools designed to meet every image analysis need. In this course, you'll be introduced to all of the features of Rekognition for image and video processing. Through examples, you'll see Rekognition used with several different programming languages and build environments to help you select the solution that best fits your needs. Security, file storage, event notification, and many other services need to come together to build any type of application with AWS. You will learn how to configure AWS services to produce a working Rekognition application. Every feature of Rekognition will be demonstrated, object and scene detection for classifying images, face detection, comparison, and recognition will be shown with working examples, and that's not all. We will look at celebrity detection, finding famous people in images, unsafe image moderation to filter unwanted adult content, and detecting text in images such as road signs and license plates. Unique to the video processing service, we will look at person tracking and pathing. This detects when a person moves, leaves, or enters a video and their location in the frame. I think you will find this course both fun and informative, and I hope you join me.
Using the Image Features of Rekognition We'll look at the image features of Rekognition. So the first thing that we're going to be doing is object and scene detection. We looked at this in the command line example in the introduction. We're going to do a more extensive programming example and process multiple images. Then we're going to go look at facial analysis. We're going to do this using the Java programming language, and we'll talk about why that's important. Then we'll look at facial recognition, which is, of course, the first thing most people think about when they think about image processing. We'll look at image moderation, or the filtering of unsafe images, and then we'll look at celebrity identification, have a little fun with that. There will be two things left that we won't cover, facial comparison, which is very similar in technique to the facial recognition, and text in image, we covered that in the introductory section. So let's go on to our first programming example.