New Delhi, Aug 30 2018 : RealNetworks India Private Limited, a 100% subsidiary of RealNetworks Inc., a Seattle, USA based leader in digital media software and services, today announced the immediate availability of SAFR™ for the India market, providing a highly accurate, facial recognition platform, architected to economically scale with high performance and rapid processing to detect and match millions of faces in real time. Utilizing artificial intelligence and machine learning, SAFR – Secure Accurate Facial Recognition, is continuously improving efficiency, accuracy, and reach.
SAFR is distinguished from other facial recognition platforms in three ways :
• World class accuracy – SAFR recognizes faces with proven 99.8 percent accuracy for Labeled Faces in the Wild (LFW), based on the University of Massachusetts benchmark. In addition, the National Institute of Standards and Technology (NIST), tested SAFR’s recognition algorithm for “Wild Faces” False Non-Match Rate (FNMR), and ranked it as one of the world’s top facial recognition algorithms.
• Extraordinary efficiency and flexibility – SAFR works seamlessly with existing IP-based cameras and readily available hardware to recognize people in real time, helping to enhance secure access and surface insights. SAFR supports both cloud and local storage. System integrators and application developers can easily integrate with the SAFR platform through RESTful API’s, an SDK, and a dashboard.
• Focus on privacy and socially positive use cases – SAFR encrypts all facial data and images to ensure privacy. When used locally, no personal or facial data is ever transmitted over the Internet.
Noriaki Takamura, Vice President and Head of APAC region who travelled from Tokyo for the SAFR launch said that, “SAFR supports numerous secure access use cases where facial recognition can replace the use of an ID badge, securely automate entry to facilities, trigger notifications, and log events for analytics. SAFR provides facial detection and tracking of many faces in a single camera feed. Each face can be selectively analyzed for age, gender, sentiment, and liveness. Faces are rapidly matched to a database of enrolled faces, returning each identity with a recognition confidence score. SAFR works with off-the-shelf IP cameras and runs on mobile devices and readily available computers.”
Bikas Jha, Country Manager for RealNetworks India, further explained that, “SAFR has been designed to scale with high performance and fast processing time, even in rural areas with very low bandwidth. Delivering best-in-class facial recognition, SAFR leverages the latest machine learning and AI techniques to detect and differentiate individuals in complex surroundings. SAFR is continuously improving and expanding in real-world environments. Building on its legacy and leadership in streaming media – including compression, media delivery, digital rights management, and efficient scalability – RealNetworks’ expertise now extends to AI, machine learning and deep neural networks: the foundation of SAFR.”
