A Professional's Guide to Troubleshooting Avigilon Facial Recognition
Avigilon's facial recognition and Appearance Search technology are powerful tools for forensic investigations and real-time security monitoring. When properly configured, these systems allow operators to rapidly locate individuals and receive critical watchlist alerts. However, when the system fails to perform as expected, it can compromise security operations.
This guide is intended for security professionals and system administrators to help diagnose and resolve common issues with the Avigilon facial recognition platform within the Avigilon Control Center (ACC) environment.
Common Symptoms of Facial Recognition Performance Issues
Identifying the specific problem is the first step toward a solution. Common performance complaints include:
- No Faces Indexed: When using Appearance Search, searches for faces return no results, even though people were clearly visible.
- Poor Recognition Accuracy: The system frequently fails to match a person's face to their profile in a watchlist or returns many incorrect potential matches.
- Failed Watchlist Alerts: A person of interest who is enrolled in a watchlist passes a camera, but no alarm is triggered in ACC.
- Slow Performance: Appearance Search queries take an excessively long time to process and return results.
- Analytics Not Running: A specific camera's overlay indicates that facial recognition or other analytics are not active.
- Environmental Challenges: The system works well in some areas but performs poorly in locations with variable lighting, high traffic, or challenging camera angles.
Systematic Troubleshooting for Avigilon Facial Recognition
Follow these professional steps to diagnose and correct issues with your Avigilon analytics system.
1. Verify System and Camera Configuration in ACC
The most common source of problems is incorrect software configuration within the Avigilon Control Center server.
- Enable Analytics on the Camera: In the ACC Client, navigate to the Setup tab and select the camera in question. Go to the 'Analytics' settings. Ensure that 'Face Detection' or the appropriate analytics mode is enabled. If this is turned off, the camera will not process or send facial data to the server.
- Check Server-Side Analytics: For some architectures, analytics are processed on the NVR or an AI appliance. Confirm that the device is licensed correctly and that the facial recognition service is running. Check the device's load to ensure it is not overwhelmed.
- Firmware and Software Versions: Ensure that your ACC server software, ACC client, and camera firmware are all updated to recent, compatible versions. Mismatched firmware can lead to unpredictable behaviour and performance issues.
2. Optimise Camera Installation and Field of View
The physical placement of the camera is a critical factor that cannot be overstated. No amount of software tuning can compensate for a poorly positioned camera.
- Camera Angle: The ideal vertical angle for a facial recognition camera is 0 to 20 degrees from the horizontal plane. The camera should be looking straight at approaching subjects, not down from a steep 'top-down' angle.
- Pixels on Target: For reliable recognition, the subject's face must be of sufficient resolution. The industry best practice is a minimum of 80 pixels between the eyes. Position cameras closer to choke points where subjects must pass.
- Avoid Obstructions: Ensure the camera's field of view is clear of physical obstructions (e.g., signs, pillars, plants) that could obscure a person's face.
3. Address Lighting and Environmental Factors
The quality of the image directly impacts the algorithm's ability to perform.
- Avoid Backlighting: Never position a camera pointing towards a primary light source, such as a bright window or doorway to the outside. This will create a silhouette effect, leaving the face in shadow.
- Ensure Even Illumination: The target area should be evenly and consistently lit. Use diffused, overhead lighting where possible. Avoid scenarios with harsh shadows falling across faces.
- WDR and IR Settings: For scenes with challenging light, ensure the camera's Wide Dynamic Range (WDR) is enabled and properly configured. At night, verify that the built-in or supplementary Infrared (IR) illuminators provide sufficient light to capture facial details without creating 'hot spots' or glare.
4. Manage Watchlists and Similarity Thresholds
If your issue is related to watchlist alerts, the problem may lie in the database or the matching logic.
- High-Quality Enrolment Photos: When adding an identity to a watchlist, use a high-resolution, passport-style photo with a neutral background. The photo should be well-lit and front-facing.
- Adjust the Similarity Threshold: In the watchlist alarm configuration, you can set a similarity threshold. This determines how close a match needs to be to trigger an alert. If you are getting no alerts, the threshold may be set too high. If you are getting too many false alarms, it may be set too low. Adjust this value incrementally and test the results.
By methodically reviewing your software settings, physical camera deployment, and environmental conditions, you can significantly improve the accuracy and reliability of your Avigilon facial recognition system.