Multi-camera re-identification system that maintains consistent identities across overlapping and non-overlapping camera networks using deep appearance embeddings.
Visylix Person Tracking is a multi-camera re-identification (Re-ID) system that fuses real-time object detection with a deep re-identification embedding model that encodes each person's visual appearance into a compact descriptor. The technology enables seamless tracking across overlapping and non-overlapping camera networks by maintaining consistent identities as individuals move through facilities, reconstructing their complete movement paths through trajectory analysis.
Core capabilities of the Person Tracking model.
Maintains unified identity across multiple cameras, even with time gaps between sightings, using 256-dimension appearance embeddings.
Uses 256-dimension embeddings capturing clothing, texture, body shape, and gait for robust identity matching across views.
Reconstructs full travel paths identifying entry/exit points, dwell times, and zone sequences for comprehensive movement analytics.
Automatically records transitions between custom-defined zones for heatmaps and flow visualizations across entire facilities.
Recovers tracks after brief obstructions using predictive motion models and appearance memory buffers.
Processes up to 30 fps per camera supporting hundreds of concurrent streams with sub-10ms matching latency per query.
Maintains identity consistency across elevator transitions and stairwell movements with configurable re-acquisition windows.
Searches historical footage for specific individuals using a single reference image across all cameras and timeframes.
Real-world applications for Person Tracking.
Maps shopper journeys from entrance to checkout, measuring dwell times at displays and optimizing store layout for conversion rate improvement.
Tracks subjects of interest across camera networks with real-time alerts for restricted zone entry and loitering behavior.
Monitors foot traffic through choke points, corridors, and concourses to prevent dangerous congestion and optimize flow.
Analyzes occupancy patterns floor-by-floor for HVAC optimization, lighting automation, and space utilization planning.
Tracks passenger flow from check-in through boarding, identifying bottlenecks and optimizing gate assignments and staffing levels.
Performance and deployment details.
Add Person Tracking to your video pipeline in minutes.
Assign the model to specific cameras with zone definitions and sensitivity settings through the web UI or API.
The model processes video frames in real time, generating structured detection events with bounding boxes and metadata.
Receive instant alerts via webhooks, trigger automated workflows, or query detections through the REST API.
See how Person Tracking is applied across different sectors.
Explore other computer vision capabilities.
Talk to our team to see this model in action on your video feeds.