Integrate face-based user verification into your applications with a simple-to-use API and enable identity verification for applications like employee badge scanning, banking or credit applications, and security.
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. 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.
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. Rekognition is a simple and easy to use API that can quickly analyze any image or video file stored in storage. Rekognition is always learning from new data, and we are continually adding new labels and facial recognition features to the service.
Immediate response for public safety and security
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.
Searchable video library
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 Lambda functions to automatically add new video labels to the search index when a new video is uploaded in storage. Then you can use this index with Elastic Search Service to quickly locate video content.
Detect unsafe video
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.
Searchable image library
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.
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.
Face-based user verification
With Rekognition, your applications can confirm user identities by comparing their live image with a reference image.
Rekognition can detect emotions that appear to be expressed on one’s face, like happy, sad, or surprised, from facial images. Rekognition can analyze live images, and send the attributes to Redshift for periodic reporting on trends for media analysis.
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.