AI facial recognition engine 'FaceMe SDK' achieves world-class authentication accuracy.

In the latest "Age Estimation Evaluation Test" conducted by NIST, the AI facial recognition engine "FaceMe" ranked 5th in the world. 【What is the NIST FATE Age Estimation Evaluation Test?】 The NIST FATE Age Estimation Evaluation Test is one of the international benchmarks for facial analysis technology conducted by the National Institute of Standards and Technology (NIST) in the United States, which evaluates the age estimation accuracy of AI algorithms using a large-scale facial image dataset. 【Evaluation Results of FaceMe】 - World Ranking: 5th FaceMe ranked 5th among 20 global vendors, demonstrating top-class accuracy in an international competitive environment. - Mean Absolute Error (MAE): 2.87 years The average error in FaceMe's estimated age is 2.87 years, with only a 0.35-year difference from the top-ranked algorithm, achieving world-class accuracy. *MAE (Mean Absolute Error): Quantifies the error in estimated age (the smaller the number, the higher the accuracy). *NIST conducted the evaluation using 1 million facial images of individuals aged 18 to 30.

In the Hanwha Vision showroom, only registered individuals can enter through high-precision facial recognition by FaceMe Security, achieving a strict access control system with a high level of security. ▶ Background and Details CyberLink and Hanwha Vision formed a partnership in 2023 to promote the seamless integration of the AI facial recognition security system "FaceMe Security" with Hanwha Vision's video management system "Wisenet WAVE," aiming to provide a multifunctional and advanced security system. With the opening of the Hanwha Vision showroom, we have implemented an access control system that integrates Hanwha Vision's AI cameras with FaceMe Security, allowing visitors to experience the technologies of both companies firsthand. - Authentication Camera: Hanwha Vision AI IR Wall Mount Camera (5MP AI IR Wall Mount Camera) - Facial Recognition System: CyberLink FaceMe Security - Main Features: Real-time detection of registered individuals' faces and automatic opening and closing of doors.

Details of the FaceMe Security 8.3 Update < Revamped UX for Action & Alert Rule Settings > Previously, individual settings were required for each action even under the same rule. By completely overhauling the UI and UX, we have transformed the operation screen to allow for intuitive and efficient configuration. ▶ Key Update Points - Multiple actions (notifications, access control, VMS integration, etc.) can now be configured under a single rule. - The settings screen has been consolidated into a single page, allowing for an overview and editing of the entire configuration at a glance. < Enhanced Integration Features with Face Terminal (Facial Recognition Terminal) > FaceMe Security integrates with the MSK Knoctoi series (Standard/Lite), enabling door opening and closing based on facial recognition results without the need for additional devices. This update allows for detailed configuration of door opening and closing rules based on location, time of day, and groups of individuals, enabling more flexible access management tailored to on-site operations. ▶ Expected Implementation Scenarios - All employees can enter the entrance, while only administrators can enter specific areas at night, etc.

Update of FaceMe Platform 6.4 < New API - Person Attribute Recognition (PAR) > A new API called "Person Attribute Recognition (PAR)" has been added, which can recognize characteristics of individuals based on appearance information other than the face. This allows for the identification of individuals using visual features such as clothing and belongings, even in situations where the face is not visible or difficult to recognize. The following information can be detected: - Age (adult/child) - Gender - Clothing (long sleeve/short sleeve) - Clothing color - Presence of hats or bags < New API - Person Re-Identification (Re-ID) > Another new API, "Person Re-Identification (Re-ID)," can be used to match individuals captured by different cameras and identify the same person. By combining this with the aforementioned Person Attribute Recognition (PAR), it is possible to match the appearance information of a person detected by one camera with footage from another camera, allowing for the identification and tracking of their location and time. This makes it particularly effective for managing wide-area surveillance in places like shopping malls and train stations. Use cases: - Identifying the location of a lost child based on age and clothing information - Tracking suspicious individuals based on gender and belongings information