Amazon Rekognition

Deep learning-based image and video analysis

Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial recognition on images and video that you provide. You can detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.

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, and requires no machine learning expertise to use. Amazon Rekognition is a simple and easy to use API that can quickly analyze any image or video file stored in Amazon S3. Amazon Rekognition is always learning from new data, and we are continually adding new labels and facial recognition features to the service.

AWS re:Invent 2017 Introducing Amazon Rekognition Video

Benefits

Easily integrate powerful image and video analysis into your app

Continually learning

Fully managed

Amazon Rekognition makes it easy to add visual analysis features to your application with easy to use APIs that don't require any machine learning expertise. Rekognition’s APIs let you request range of features including object detection, facial recognition, and person tracking.

The service is continually trained on new data to expand its ability to recognize objects, scenes, and activities to improve its ability to accurately recognize. With Amazon Rekognition, your applications take advantage of these continual improvements automatically.

Amazon Rekognition provides consistent response times regardless of the volume of requests you make. Your application latency remains consistent, even as your request volume increases to tens of millions of requests.

Batch and real-time analysis

Low cost

You can run real-time analysis on video from Amazon Kinesis Video Streams or analyze images as they are uploaded to Amazon S3. For large jobs, Amazon Rekognition can work together with AWS Batch process and analyze thousands of images or videos stored in Amazon S3.

With Amazon Rekognition, you only pay for the number of images, or minutes of video, you analyze and the face data you store for facial recognition. There are no minimum fees or upfront commitments.

Key Features

Object, scene, and activity detection

Object, scene, and activity detection

With Amazon Rekognition, you can identify thousands of objects (e.g. bike, telephone, building) and scenes (e.g. parking lot, beach, city). When analyzing video, you can also identify specific activities happening in the frame, such as "delivering a package" or "playing soccer".

 

Facial recognition

Facial recognition

Rekognition’s fast and accurate search capability allows you to identify a person in a photo or video using your private repository of face images.

 

 

Facial analysis

Facial analysis

You can analyze the attributes of faces in images and videos you provide to determine things like happiness, age range, eyes open, glasses, facial hair, etc. In video, you can also measure how these things change over time, such as constructing a timeline of the emotions of an actor.

 

Pathing

Pathing

You can capture the path of people in the scene when using Amazon Rekognition with video files. For example, you can use the movement of athletes during a game to identify plays for post-game analysis.

 

Unsafe content detection

Unsafe content detection

Amazon Rekognition helps you identify potentially unsafe or inappropriate content across both image and video assets and provides you with detailed labels that allow you to accurately control what you want to allow based on your needs.

 

Celebrity recognition

Celebrity recognition

You can quickly identify well known people in your video and image libraries to catalog footage and photos for marketing, advertising, and media industry use cases.

 

Text in images

Text in images

Specifically built to work with real world images, Rekognition can detect and recognize text from images, such as street names, captions, product names, and license plates.

Featured Rekognition Customers

Rekognition Video Use Cases

Immediate Response for Public Safety and Security

Amazon Rekognition Video allows you to create applications that help find missing persons in social media video content. By recognizing their faces against a database of missing persons that you provide, you can accurately flag matches and speed up a rescue operation.

Example: Finding Missing Persons on Social Media
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Searchable Video Library

Amazon Rekognition Video automatically generates metadata from uploaded videos so you can create a search index for names of celebrities and their time of appearance. You can keep the index current by using AWS Lambda functions to automatically add new video labels to the search index when a new video is uploaded in Amazon S3. Then you can use this index with Amazon Elastic Search Service to quickly locate video content.

Example: Celebrity Detection in User Submitted Content
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Detect Unsafe Video

Amazon Rekognition Video allows organizations managing user-generated content, such as social media or dating apps, to automatically detect explicit or suggestive content in videos and create their own rules around what is appropriate for the culture and demographics of their users.

Example: Filtering User Generated Content
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Rekognition Image Use Cases

Searchable image library

Amazon Rekognition makes images searchable so you can discover objects and scenes that appear within them. You can create an AWS Lambda function that automatically adds newly detected image labels directly into an Elasticsearch search index when a new image is uploaded into S3.

Example: Real Estate Property Search
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Image Moderation

Amazon Rekognition allows you to automatically detect inappropriate content in images using the Image Moderation API. The API returns a confidence score for a detailed set of content categories, which allows you to create your own rules around what is appropriate for the culture and demographics of your users.

Example: Moderating User Uploaded Images
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Face-Based User Verification

With Amazon Rekognition, your applications can confirm user identities by comparing their live image with a reference image.

Example: Employee Badge Scan
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Sentiment Analysis

Amazon Rekognition can detect emotions like happy, sad, or surprised from facial images. Rekognition can analyze live images, and send the emotion attributes to Redshift for periodic reporting on trends for each store location.

Example: Retail Store Sentiment Analysis
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Facial Recognition

Amazon Rekognition makes it easy to search your image collection for similar faces by storing face metadata, using the IndexFaces API function. You can then use the SearchFaces function to return high confidence matches. A face collection is an index of faces, that you own and manage.

Example: Find Images of Friends
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Celebrity Recognition

Amazon Rekognition's RecognizeCelebrities API uses neural network-based models to allow you to search photo libraries to automatically identify thousands of individuals who are famous, noteworthy, or prominent in their field with high scale and high accuracy. You can then send the celebrity’s name, id, and image id, into an Amazon Elasticsearch search index to make the images searchable for celebrities.

Example: Searching for Celebrity Images in Image Archives
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Learn more about Amazon Rekognition

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