Rekognition Video is a deep learning powered video analysis service that tracks people, detects activities, and recognizes objects, celebrities, and inappropriate content. Amazon Rekognition Video can detect and recognize faces in live streams. Rekognition Video analyzes existing video stored in Amazon S3 and returns specific labels of activities, people and faces, and objects with time stamps so you can easily locate the scene. It can also perform facial recognition on live video from Amazon Kinesis Video Steams. For people and faces, it also returns the bounding box, which is the specific location of the person or face in the frame. Rekognition Video eliminates manual cataloging of video which is expensive, error-prone, and hard to scale.
Find out more about Amazon Rekognition Video features, benefits and use cases with this explainer video.
Amazon Recognition Video can analyze live video streams in real time to detect and recognize faces. By providing a stream from Amazon Kinesis Video Streams as an input to Rekognition Video, you can perform facial recognition against collections of up to tens of millions of faces with very low latency. For public safety applications, this helps to enable timely and accurate crime prevention. For batch processing use cases, Amazon Recognition video can also analyze previously recorded video data stored in Amazon S3.
With Rekognition Video, you can track the position of each person in a video. TrackPersons API detects persons and how they move even when the camera is in motion. It can also maintain tracking even when a person’s face is blocked, or as the whole person goes in and out of the scene. TrackPersons API returns time segments and confidence results. In public safety, this makes monitoring and investigating persons of interest easy and accurate. For retail applications, this allows you to generate customer insights, such as how customers move across aisles in a store or how long they are waiting in checkout lines.
Rekognition Video allows you to perform real time face searches against collections of tens of millions of faces. Using the CreateCollection API, you can easily create a face collection with vectors representing facial features. Rekognition then searches the face collection for visually similar faces throughout your video. Rekognition will return results, so you can display likely matches in your application. For security and public safety applications, this helps identify persons of interest against a collection of millions of faces in real-time, enabling timely and accurate crime prevention.
With Rekognition Video, you can locate faces that appear in a video and analyze their attributes, such as whether the face is smiling, the eyes are open, and emotions. Using the DetectFaces API, Rekognition Video will return the landmark points: left eye, right eye, nose, left corner of the mouth, and right corner of the mouth. This position, along with the timestamps, can be used to easily track user sentiment over time and it enables you to build your own filtering applications with features such as automatic face frames, highlights, or crops.
Rekognition Video enables you to automatically identify thousands of objects such as vehicles or pets, scenes like a city, beach, or wedding; and activities such as delivering a package or dancing. Rekognition Video relies on motion in the video to accurately identify complex activities, such as “blowing out a candle” or “extinguishing fire”.
Rekognition Video enables you to detect explicit and suggestive content so that you can filter videos based on your applications requirements. Rekognition provides a range of different moderation levels, from explicit to suggestive, so you can apply the correct moderation level for you audience.
With Rekognition Video, you can detect and recognize when and where well known persons appear in a video. The time-coded output includes the name and unique id of the celebrity, and URLs pointing to related content for the celebrity, for example, the celebrity's IMDB link. This allows you to index and search digital video libraries for use cases related to your specific marketing and media needs.
Amazon Rekognition can be accessed using the Amazon Rekognition API, AWS Management Console, and the AWS command-line interface (CLI). The console, API, and CLI provide the ability to use the Rekognition APIs to detect labels, analyze faces, compare faces, and find a face. AWS Lambda has blueprints for Rekognition that make it easy to initiate image analysis based on events in your AWS data stores such as Amazon S3 and Amazon DynamoDB.
Amazon Rekognition is integrated with AWS Identity and Access Management (IAM). IAM policies can be used to control access to the Amazon Rekognition API as well as manage resource-level permissions for your account.