XVeillance Facial Recognition stands out as one of the most precise face recognition algorithms, earning a top-ranking position in the evaluation conducted by the National Institute of Standards and Technology (NIST) among 129 facial recognition vendors.

XVeillance's video stream search engine analyzes human faces, vehicles, and license plates in real-time or recorded footage. It aids in identifying individuals, tracking vehicle movements, and reading license plate numbers. This technology is invaluable for law enforcement, public safety, security, and loss prevention applications, providing crucial data for investigations, traffic monitoring, access control, and preventing theft or other losses.

How XVeillance Technology Platform Works

1. Real-time Person Detection & Face Recognition

A real-time video processing pipeline starts with capturing and pre-processing CCTV streams. Frames are extracted every 100 milliseconds to balance efficiency and accuracy. Image enhancement techniques like denoising and contrast adjustment improve facial detection, ensuring reliable identification even in poor lighting or noisy conditions. This step prepares the data for recognition and transmission.

2: Detect and Extract Faces

After pre-processing, AI-powered XVeillance algorithm detects faces in real time. Detected faces are then cropped and aligned for consistency, enhancing recognition accuracy. Our deep learning model converts these images into unique numerical embeddings, allowing fast and reliable identification across frames. This streamlined process ensures precise face recognition, even in dynamic environments.

3: Face Comparison with Registered Images

XVeillance maintains a database of registered individuals, storing face embeddings for employees, VIPs, or flagged security risks. When a new face embedding is extracted, it is compared against the database using similarity measures such as Cosine Similarity, Euclidean Distance, or deep learning-based scoring. If the similarity score surpasses a predefined threshold (e.g., 0.8), the system confirms a match, enabling seamless identification and real-time alerts when necessary.

4: Trigger Alerts for Matches on Mobile Phone

When a match is found, the system instantly triggers an alert, capturing key metadata such as the detected face image, confidence score, timestamp, location, and camera ID. These alerts are sent in real-time to security personnel via a mobile app or web dashboard, ensuring quick response. Additionally, a web application provides corporate administrators with a comprehensive view of reports and analytics, enabling organization-wide monitoring and decision-making.