Error-free Real-time Face Recognition Solution | ALCHERA

 

ALCHERA Inc. is a Korean company well-recognized in the USA and Vietnam in the area of Visual AI to be applicable to real-time face recognition solution.

Since Face recognition is highly sensitive to pose variations, the pose correction is essential process and could be achieved by means of efficient techniques aiming to rotate the face and/or to align it to the image's axis as detailed in reference. 

Face recognition solution has received a lot of attention from both research and industry communities  3d Face Stickers and Masking Technology

ü  Due to its fascinating range of scientific challenges as well as rich possibilities of commercial applications

ü  Particularly in the context of biometrics/forensics/security

ü  And, more recently, in the areas of multimedia and social media

Face recognition is one of the most powerful processes in biometric systems and is extensively used for security purpose in tracking and surveillance, attendance monitoring, passenger management at airports, passport de‐duplication, border control, and high-security access control as developed by companies like ALCHERA

Error-free assured performance of ALCHERA face recognition solution 

ALCHERA provides a real-time face recognition solution and a face-based video retrieval solution that can be easily installed on mobile devices, servers, and cloud systems, regardless of the type of OS or device. Such face recognition technology is a biometric technology capable of automatically detecting facial areas and extracting unique patterns, as well as identifying and verifying a person from a digital image or video. data management technology

ALCHERA’s Face recognition solution aims to identify people in images or videos using pattern recognition techniques. Automated face recognition is widely used in applications ranging from social media to advanced authentication systems. While various techniques for face recognition are well established, the automatic recognition of faces captured by digital cameras in an unconstrained, real‐world environment is still very challenging since it involves important variations in both acquisition conditions as well as in facial expressions and in pose changes.