Amazon Rekognition

Quickly and accurately identify unsafe or inappropriate content across image and video assets based on general or business-specific standards

Store face vectors and user vectors for face and user search functionality

Identify well-known people to catalog photos and footage for media, marketing, and advertising

Detect faces appearing in images and videos and recognize attributes such as open eyes, glasses, and facial hair for each face

Detect real users and deter bad actors using spoofs in seconds during facial verification

Search and match faces against stored face metadata to identify individuals in collections

Use facial comparison and analysis in user onboarding and authentication workflows to remotely verify identity of opted-in users

Detect image quality and dominant colors in images

Detect objects, scenes, activities, landmarks, dominant colors, and image quality

Train custom models for object and scene detection specific to business needs using AutoML

Detect custom objects such as brand logos using automated machine learning (AutoML) to train models with as few as 10 images

Detect people in images and videos

Detect the presence of protective equipment like hard hats, goggles, and masks

Extract skewed and distorted text from images and videos of street signs, social media posts, and product packaging

Detect shot transitions and key segments in videos

Analyze videos stored in Amazon S3 with multiple API capabilities

Process real-time video streams from Kinesis Video Streams for up to 120 seconds per event

Detect key segments in videos such as black frames, start or end credits, slates, color bars, and shots