RETROSPECTIVE FACIAL RECOGNITION
In today's fast-paced world, ensuring public safety is a leading priority for organisations worldwide. The need for advanced technology to combat crime has led to the development of innovative tools like FAICEMATCH, a Retrospective Facial Recognition aid. This cutting-edge solution goes beyond traditional methods, helping to match cases and identify known Organised Crime Gangs, Violent Offenders and Lone Thieves with unprecedented accuracy.
Confidently identify individuals.
- Enhanced Investigative Efficiency
- Retrospective Facial Recognition allows law enforcement to revisit existing CCTV footage photos, or videos to identify suspects retrospectively. This capability significantly expedites investigations, leading to faster case resolutions.
- Improved Accuracy
- The advanced algorithms used in this tool provide higher accuracy rates in facial recognition, reducing the chances of false positives and minimising the risk of wrongful detains or deters.
- Organised Crime Gang Identification
- By comparing facial data against databases of known Subjects of Interest, organisations can uncover links and connections that may have otherwise gone unnoticed.
- Violent Offender Identification
- Identifying violent offenders swiftly is crucial for public safety. Retrospective Facial Recognition aids in identifying and tracking these individuals, making communities safer.
- Preventative Measures
- With its ability to identify suspects and potential threats quickly, you are able proactive steps to prevent future criminal activities, thus deterring crime.
Retrospective Facial Recognition, as opposed to live facial recognition, often aligns more closely with GDPR and data privacy regulations. In Retrospective Facial Recognition, images or videos are analysed after they have been captured and stored, typically for specific security or identification purposes.
This approach allows for greater control over data access, storage, and consent, as individuals can be informed and provide consent before their data is used for recognition. Moreover, GDPR principles, such as the right to be forgotten and data minimization, can be more easily applied to retrospective systems, as the data can be deleted or anonymized once the intended purpose is fulfilled.
In contrast, Live Facial Recognition may raise privacy concerns about continuous surveillance, while Retrospective Facial Recognition focuses on specific investigative leads and historical data, reducing privacy implications.