Facial recognition vendor 3DiVi has released version 1.16.0 of its Biometric Anti-Fraud (BAF) platform, adding expanded attempt-level diagnostics and more configurable user interface logic for face capture workflows.
The update, dated January 27 in the company’s release notes, includes an expanded list of data errors on the Attempts page in the BAF Dashboard, providing operators with more granular visibility into biometric capture failures. The release also adds the ability to redefine UI logic for face border rendering, face masks based on keypoints, and Motion Control direction hints.
The changes follow 3DiVi’s BAF 1.15 release in December, which focused on deepfake detection and privacy compliance enhancements.
Improvements to dashboard diagnostics and attempt tracking can help operators troubleshoot failures, tune capture experiences, and improve completion rates in deployments that rely on liveness detection to distinguish live biometric samples from spoofed presentations.
The UI customization features address usability, accessibility, and compliance requirements across different deployments. Operators can now configure how face borders and masks are rendered based on facial keypoints, and customize direction hints for motion-based liveness checks. This flexibility allows integrators to adapt the biometric capture interface to specific use cases, from financial services onboarding to government credential issuance.
BAF 1.16.0 also updates the underlying Face SDK library to version 3.29.0 and adds the ability to disable unnecessary ingress for modules. The release includes updated locales for the web component and removes the overlay settings block from motion control and face bestshot configuration blocks.
Bug fixes address issues with camera ID settings when form completion is required to determine applicant status, and an issue where invalid integration IDs caused the component to continuously attempt log connections. These fixes improve stability in production deployments where multiple cameras or complex workflow configurations are common.
The configuration changes mean the background for face frames is now handled by defining a custom version of the FaceBorder UI element, rather than through overlay settings in motion control or face bestshot configuration blocks. This architectural shift gives developers more direct control over the visual presentation of face capture interfaces.
The expanded diagnostics capabilities in the dashboard reflect growing demand for detailed analytics in biometric authentication systems. As organizations deploy facial recognition for remote identity verification, the ability to analyze failure patterns and optimize capture parameters becomes critical for maintaining high completion rates while preserving security standards.
Sources: 3DiVi documentation
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By the ID Tech Editorial Team
