Amazon Rekognition makes it easy to add image and video analysis to your applications.

You just provide an image or video to the Amazon Rekognition API, and the service can identify objects, people, text, scenes, and activities.

It can detect any inappropriate content as well.

Amazon Rekognition also provides highly accurate facial analysis, face comparison, and face search capabilities.

You can detect, analyze, and compare faces for a wide variety of use cases, including user verification, cataloging, people counting, and public safety.

Amazon Rekognition is based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily.

It requires no machine learning expertise to use. Amazon Rekognition includes a simple, easy-to-use API that can quickly analyze any image or video file that’s stored in Amazon S3.

Searchable image and video libraries – Amazon Rekognition makes images and stored videos searchable so you can discover objects and scenes that appear within them.

Face-based user verification – Amazon Rekognition enables your applications to confirm user identities by comparing their live image with a reference image.

Detection of Personal Protective Equipment - Amazon Rekognition detects Personal Protective Equipment (PPE) such as face covers, head covers, and hand covers on persons in images. You can use PPE detection where safety is the highest priority.

Sentiment and demographic analysis – Amazon Rekognition interprets emotional expressions such as happy, sad, or surprise, and demographic information such as gender from facial images. Amazon Rekognition can analyze images, and send the emotion and demographic attributes to Amazon Redshift for periodic reporting on trends such as in store locations and similar scenarios.

Facial Search – With Amazon Rekognition, you can search images, stored videos, and streaming videos for faces that match those stored in a container known as a face collection. A face collection is an index of faces that you own and manage. Searching for people based on their faces requires two major steps in Amazon Rekognition:

1. Index the faces.

2. Search the faces.

Unsafe content detection – Amazon Rekognition can detect adult and violent content in images and in stored videos. The API also returns a hierarchical list of labels with confidence scores. These labels indicate specific categories of unsafe content, which enables granular filtering and management of large volumes of user-generated content (UGC).

Celebrity recognition – Amazon Rekognition can recognize celebrities within supplied images and in videos.

Text detection – Amazon Rekognition Text in Image enables you to recognize and extract textual content from images. Text in Image supports most fonts, including highly stylized ones. It detects text and numbers in different orientations, such as those commonly found in banners and posters.

Custom labels– With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can find your logo in social media posts, identify your products on store shelves, classify machine parts in an assembly line, distinguish healthy and infected plants, or detect animated characters in videos.

You start analyzing a streaming video by starting an Amazon Rekognition Video stream processor and streaming video into Amazon Rekognition Video.

An Amazon Rekognition Video stream processor allows you to start, stop, and manage stream processors.

You create a stream processor by calling CreateStreamProcessor.

The request parameters include the Amazon Resource Names (ARNs) for the Kinesis video stream, the Kinesis data stream, and the identifier for the collection that's used to recognize faces in the streaming video.

It also includes the name that you specify for the stream processor.

You need a Kinesis video stream for sending streaming video to Amazon Rekognition Video.

An Amazon Rekognition Video stream processor to manage the analysis of the streaming video.

A Kinesis data stream consumer to read the analysis results that Amazon Rekognition Video sends to the Kinesis data stream.

Amazon Rekognition Image

Amazon Rekognition Custom Labels

Amazon Rekognition Video Stored Video

Amazon Rekognition Video Streaming Video

Content