Why Choose Attendance Pro?
Our platform combines cutting-edge AI with intuitive design to solve real-world attendance challenges.
Lightning Fast
Recognize employees in under 0.2 seconds. Ensure smooth entry flows without queues.
Anti-Spoofing
Advanced liveness detection prevents fraud using photos or videos. Security you can trust.
Smart Analytics
Gain insights into attendance trends, punctuality, and productivity with detailed reports.
Face Ingestion Pipeline
A secure, multi-stage process that transforms a raw user image into an encrypted, privacy-preserving vector identity.
1. Face Detection
1. Face Detection
- Input AnalysisThe uploaded image or camera snapshot is processed using Tiny Face Detector to locate faces in the frame.
- Integrity CheckThe system verifies exactly one clear face is present to ensure high-quality data ingestion and avoid ambiguity.
2. Landmark Alignment
2. Landmark Alignment
- Landmark DetectionA 68-point facial landmark model detects key regions such as eyes, nose, and jawline with high precision.
- Geometric AlignmentThe face is aligned and normalized to correct for tilt, rotation, and scale, ensuring consistent feature extraction.
3. Feature Extraction
3. Feature Extraction
- Deep Learning AnalysisThe aligned face is passed through a Deep ResNet model trained on millions of faces.
- Unique EmbeddingA 128-dimensional face descriptor (embedding) is generated to uniquely represent the user's identity mathematically.
4. Store in MongoDB
4. Store in MongoDB
- EncryptionThe 128-D face descriptor is encrypted using industry-standard protocols before storage.
- Secure StorageData is stored in MongoDB alongside user metadata. Actual face images are optional, ensuring privacy.
Face Detection Pipeline
An ultra-low latency inference loop running completely on the client device to ensure instant and secure attendance marking.
1. Real-Time Face Detection
1. Real-Time Face Detection
- Live ScanningLive video frames are scanned continuously using Tiny Face Detector.
- High PerformanceFaces are detected in milliseconds, ensuring instant responsiveness even on low-power devices.
2. Landmark Alignment
2. Landmark Alignment
- Instant MappingThe detected face is instantly aligned using the 68-point landmark model.
- Pose NormalizationHead pose, rotation, and scale variations are normalized to match stored templates.
3. Feature Extraction
3. Feature Extraction
- Live ExtractionThe aligned face is passed through the Deep ResNet model to generate a live descriptor.
- On-Device ProcessingComputation happens efficiently, ensuring privacy and speed.
4. Euclidean Distance Matching
4. Euclidean Distance Matching
- Vector ComparisonThe live descriptor is compared mathematically with stored embeddings in the database.
- Threshold VerificationIf the calculated distance is less than 0.6, a match is confirmed with high confidence.
5. Attendance Action
5. Attendance Action
- System UpdateOn successful match, attendance is marked, and entry time metadata is instantly stored.
- Identity VerifiedThe user receives immediate visual confirmation of their successful identification.
