Amazon Rekognition
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.
With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.
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Oz Liveness
Oz Liveness is a leading facial recognition and authentication software used by private and public organizations across the globe to lower the risk of biometric fraud by preventing deepfake and spoofing attacks with 100% accuracy.
The technology has been validated by the industry’s most rigorous testing standard, ISO 30107-3 iBeta level 1 and 2 certifications. It helps organizations validate they are dealing with a real person within seconds, lowering compliance and fraud risks.
Oz Liveness features advanced algorithms able to detect many forms of biometric spoofing, including 3D and 2D masks and photos along with photos or videos displayed on a mobile or a laptop screen.
On-device Liveness detection and face biometry checks allow to use of a phone as a personal biometric device. No data is sent to the server from the device and stays in the customer's hands. On-device Liveness is perfect in any customer’s use case, improving the reachability and stability of the services .
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Face SDK
Facial and body recognition library for server, mobile and embedded solutions requiring image and streaming video processing:
- Face Identification and Verification. Search for face matches, 1:N identification and 1:1 verification scenarios
- Real Time Video Processing. SDK components enable face detection, tracking and matching from video stream in real time
- Face Quality Control. Dozens of quality checks such as head rotation, blur, flare, face size, eyes and mouth openness, and more
- Face Landmarks. Detect size, pitch, roll, yaw, and up to 468 facial landmarks
- Gender, Age, Emotions Recognition. Detects 7 basic human emotions on photos or video stream
- Passive and Active Liveness. Comprehensive Liveness Detection algorithms against face or video spoofing
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Betaface
We offer ready components, such as face recognition SDKs, as well as custom software development services and hosted web services with a focus on image and video analysis, faces and objects recognition. Our technology is used by video and images archives, web advertising and entertainment projects, media content producers, video surveillance and security software solutions, end user and b2b software developers and others. Betaface facial recognition suite embraces whole range of complex operations from fundamental face detection through face recognition (identification, verification or 1:1, 1:N matching) to biometric measurements, face analysis, face and facial features tracking on video, age, gender, ethnicity and emotion recognition, skin, hair and clothes color detection, hairstyle shape analysis and facial features shape description. Our technology is used by video and images archives, web advertising and entertainment projects.
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