Dubai, United Arab Emirates – HID, the worldwide leader in trusted identity and biometric solutions, is excited to announce that its advanced imaging technology and U.ARE.U™ Camera Identification System now works with Amazon Rekognition, a fully managed computer vision cloud service in the identity verification process.
The combination of HID’s U.ARE.U camera with Amazon Rekognition will enable customers to achieve superior results. HID’s technology for capturing faces across widely changing light conditions, backgrounds, expressions, and demographics, allows for maximum flexibility in deployment. In addition, the camera leverages several sensors onboard to offer built-in liveness detection and can be deployed in ADA-compliant use cases, leveraging its wide vertical field of view. These features make it particularly suited for self-serve and POS environments found in hospitality, healthcare, sports, entertainment, retail, banking, government, transportation, and beyond.
HID now works with the following Amazon Rekognition capabilities:
- Amazon Rekognition Face Detection: predicts attributes such as bounding box size, pose, brightness, sharpness, eyes open, mouth open, and eyeglasses worn to determine face quality.
- Amazon Rekognition Face Comparison: measures the similarity of two faces to help you determine if they are the same person.
- Amazon Rekognition Face Index and Search: creates a face collection of existing users and searches new user selfie pictures.
“This successful collaboration is an example of our commitment to innovation and continued focus on creating value through our technologies,” said Vito Fabbrizio, Managing Director of the Biometrics Business Unit, Extended Access Technologies at HID. “We are proud to work with Amazon’s face recognition technology to meet the best possible performance in challenging environments, such as self-serve and point of sale. The goal is to enable the best possible customer experience without compromising on accuracy and security.”
To learn more about HID’s U.ARE.U camera, watch the video. For more details about Amazon Rekognition, visit the website.
