The Science Behind Facial Embeddings: How Your Face Becomes Data
The Science Behind Facial Embeddings: How Your Face Becomes Data
Dec 28, 2024
Dec 28, 2024
A Deep Dive Into the AI That Powers Glide’s Real-Time Recognition
A Deep Dive Into the AI That Powers Glide’s Real-Time Recognition


Facial recognition is often misunderstood as simple image matching. In reality, it relies on a much more advanced process, rooted in machine learning and computer vision. At Glide, our system does not store or compare actual photos. Instead, it uses a mathematical structure known as a facial embedding.
So, what exactly happens when a guest checks in with Glide?
Step 1: Facial Detection and Landmarking
First, the system detects the face and identifies key landmarks such as the eyes, nose, and mouth. This stage is handled by a neural network that maps out facial geometry with precision.
Step 2: Feature Extraction via Convolutional Neural Networks (CNNs)
Once the facial structure is mapped, a convolutional neural network extracts unique features from the face. These features are not images or pixels. They are patterns, distances, and ratios that define the face mathematically.
Step 3: Embedding Creation
The extracted features are then encoded into a facial embedding, which is a vector of numbers, typically 128 to 512 dimensions in length. This vector is unique to each individual and is nearly impossible to reverse-engineer into a face.
This is what Glide uses for recognition. Not your photo. Not your ID. Just encrypted numerical data.
Step 4: Real-Time Comparison
When a guest approaches a Glide kiosk or camera, the system generates a new embedding from their live image and compares it against the stored embedding created at registration. If the two vectors fall within a certain threshold, the match is confirmed in milliseconds.
Privacy Built In
Because Glide does not store photos, only embeddings, your biometric identity remains secure. These embeddings are anonymized, encrypted, and discarded immediately after verification unless explicitly authorized for ongoing use.
This approach makes Glide compliant with modern biometric regulations such as GDPR and BIPA, and ensures that trust and safety are built into every interaction.
Facial recognition is not about watching you. It is about verifying you , safely, privately, and instantly.
Glide turns your face into data, not risk.
Facial recognition is often misunderstood as simple image matching. In reality, it relies on a much more advanced process, rooted in machine learning and computer vision. At Glide, our system does not store or compare actual photos. Instead, it uses a mathematical structure known as a facial embedding.
So, what exactly happens when a guest checks in with Glide?
Step 1: Facial Detection and Landmarking
First, the system detects the face and identifies key landmarks such as the eyes, nose, and mouth. This stage is handled by a neural network that maps out facial geometry with precision.
Step 2: Feature Extraction via Convolutional Neural Networks (CNNs)
Once the facial structure is mapped, a convolutional neural network extracts unique features from the face. These features are not images or pixels. They are patterns, distances, and ratios that define the face mathematically.
Step 3: Embedding Creation
The extracted features are then encoded into a facial embedding, which is a vector of numbers, typically 128 to 512 dimensions in length. This vector is unique to each individual and is nearly impossible to reverse-engineer into a face.
This is what Glide uses for recognition. Not your photo. Not your ID. Just encrypted numerical data.
Step 4: Real-Time Comparison
When a guest approaches a Glide kiosk or camera, the system generates a new embedding from their live image and compares it against the stored embedding created at registration. If the two vectors fall within a certain threshold, the match is confirmed in milliseconds.
Privacy Built In
Because Glide does not store photos, only embeddings, your biometric identity remains secure. These embeddings are anonymized, encrypted, and discarded immediately after verification unless explicitly authorized for ongoing use.
This approach makes Glide compliant with modern biometric regulations such as GDPR and BIPA, and ensures that trust and safety are built into every interaction.
Facial recognition is not about watching you. It is about verifying you , safely, privately, and instantly.
Glide turns your face into data, not risk.