Fraunhofer Institute for Computer Graphics Research IGD
As part of the ATHENE project Secure Identity Management, a solution was developed that combines facial recognition with head-mounted displays. This provides security forces with targeted support during operations – with more relevant information, fewer redundant checks, and significant relief in the decision-making process.
The Challenge: Security in Crowds
Large-scale events such as festivals, sporting events, or border controls present security forces with complex tasks. On the one hand, the flow of people must be organized quickly and smoothly; on the other hand, a high level of security is required. Traditional methods quickly reach their limits – they are time-consuming, labor-intensive, and offer only limited options for continuous real-time monitoring.
The Project Approach: Seamless Identification through Facial Recognition
Within ATHENE, we developed an innovative solution: seamless identification in high-throughput crowd management. The core idea is the combination of robust facial recognition with head-mounted displays (HMDs). This enables security personnel to receive additional information directly in their field of vision in real time: whether a person has already been checked, whether they are flagged as suspicious, or whether a further check is necessary. Attention is thus directed toward truly relevant cases. This makes it possible to enhance the quality of security checks without disrupting the flow of people. It represents a significant advancement for event security, border security, and public safety operations.
Efficient Real-Time Facial Recognition
The solution enables scalable, discreet identification in mobile environments. Marked individuals – for example, wanted persons or those classified as high-risk – can be recognized immediately. At the same time, the system registers unknown individuals, documents repeated appearances, and actively alerts security forces. This gives them greater situational awareness and allows for more informed decision-making.
Technical Implementation: From Registration to Real-Time Analysis
At the core is a facial recognition platform that allows authorized entities to register image material offline. These data are processed using deep learning models and linked to metadata such as names or IDs. During deployment, the system automatically recognizes faces, applies color-coded markers, and can also track unknown individuals over time. Every sighting is logged and enriched with contextual information, making suspicious movement patterns visible.
More Security and Efficiency in Operations
The research results demonstrate how technology can specifically support personnel in the field. Authorities, security services, and event organizers benefit from scalable identification, gain better information, can respond more quickly, and therefore assess risks more accurately and make better-informed decisions. The result: greater public safety – along with improved efficiency in operational use.
