3DiVi Launches Cam QA Tool That Instantly Checks Camera Positioning and Configuration in Face Recognition-Driven Video Analytics Projects
Face recognition failing? It’s probably not the algorithm — it’s cameras. In projects across retail, banking, and safe cities, poor camera setup quietly kills performance and inflates costs. But what if integrators and operators could fix that before it becomes a disaster? 3DiVi’s new automated camera audit tool uncovers hidden issues, boosts face recognition accuracy, and saves serious budget — already helping integrators speed up deployments and avoid costly mistakes.
Covina, CA, May 07, 2025 --(PR.com)-- Face recognition performance in Video Analytics systems — whether for law enforcement, safe cities, retail, banking, or access control — often suffers due to improper camera placement, poor lighting, and environmental factors like dust or glare. These issues can cause a significant drop in accuracy, leading to failed identifications and costly project overruns. Despite the importance of correct setup, these problems are often overlooked, only becoming apparent after deployment.
3DiVi Cam QA Tool addresses these challenges by automatically analyzing both live and recorded camera footage. The tool evaluates 19 key parameters that directly impact face recognition performance and generates detailed reports with actionable recommendations. Whether during initial installation or post-deployment, 3DiVi Cam QA ensures cameras are optimally placed and configured for maximum face recognition accuracy.
Key Benefits:
For video analytics system owners and operators: An objective way to validate face recognition performance at the acceptance stage and track any decline in quality over time.
For video analytics system integrators: A reliable tool to reduce the risk of client complaints about poor face recognition, choose the right equipment for specific video analytics tasks, monitor installation teams, optimize project workflows, and improve the technical expertise of your team.
How It Works:
Upload a live camera feed (RTSP stream) or a 30-minute field video.
The tool analyzes 30-50 unique faces for optimal performance.
Receive a detailed PDF report showing 19 performance parameters, with suggestions for improvements.
Real-World Examples:
Case #1: Saved $59,000 on Cameras Without Sacrificing Performance
A VMS integrator used 3DiVi Cam QA to review their camera fleet and found that their 4K units weren’t improving face recognition accuracy. By switching to lower-cost 2K and Full HD cameras, they saved $59,000 — 17% of their project budget —without sacrificing performance.
Case #2: Accuracy jumped from 47% to 96%
A public safety department conducted a post-deployment check with 3DiVi Cam QA a year after installing their camera system. Issues like dust, poor lighting, and minor misalignments had reduced accuracy to just 47%. After quick adjustments, accuracy increased to 96%, significantly boosting identification rates for ongoing cases.
Face recognition accuracy doesn't just rely on the algorithm — it also depends on how well your cameras are set up. With automated camera audit organizations can optimize their camera systems, reduce hardware costs, and improve face identification rates.
More information about 3DiVi Cam QA: https://3divi.ai/special-offers/cam-qa-for-integrators
About 3DiVi Inc.
3DiVi Inc., founded in 2011, is one of the leading international developers of AI and machine learning (ML) technologies for computer vision. The company's computer vision algorithms cover face recognition, body and skeletal tracking, spatial understanding and object recognition.
3DiVi Cam QA Tool addresses these challenges by automatically analyzing both live and recorded camera footage. The tool evaluates 19 key parameters that directly impact face recognition performance and generates detailed reports with actionable recommendations. Whether during initial installation or post-deployment, 3DiVi Cam QA ensures cameras are optimally placed and configured for maximum face recognition accuracy.
Key Benefits:
For video analytics system owners and operators: An objective way to validate face recognition performance at the acceptance stage and track any decline in quality over time.
For video analytics system integrators: A reliable tool to reduce the risk of client complaints about poor face recognition, choose the right equipment for specific video analytics tasks, monitor installation teams, optimize project workflows, and improve the technical expertise of your team.
How It Works:
Upload a live camera feed (RTSP stream) or a 30-minute field video.
The tool analyzes 30-50 unique faces for optimal performance.
Receive a detailed PDF report showing 19 performance parameters, with suggestions for improvements.
Real-World Examples:
Case #1: Saved $59,000 on Cameras Without Sacrificing Performance
A VMS integrator used 3DiVi Cam QA to review their camera fleet and found that their 4K units weren’t improving face recognition accuracy. By switching to lower-cost 2K and Full HD cameras, they saved $59,000 — 17% of their project budget —without sacrificing performance.
Case #2: Accuracy jumped from 47% to 96%
A public safety department conducted a post-deployment check with 3DiVi Cam QA a year after installing their camera system. Issues like dust, poor lighting, and minor misalignments had reduced accuracy to just 47%. After quick adjustments, accuracy increased to 96%, significantly boosting identification rates for ongoing cases.
Face recognition accuracy doesn't just rely on the algorithm — it also depends on how well your cameras are set up. With automated camera audit organizations can optimize their camera systems, reduce hardware costs, and improve face identification rates.
More information about 3DiVi Cam QA: https://3divi.ai/special-offers/cam-qa-for-integrators
About 3DiVi Inc.
3DiVi Inc., founded in 2011, is one of the leading international developers of AI and machine learning (ML) technologies for computer vision. The company's computer vision algorithms cover face recognition, body and skeletal tracking, spatial understanding and object recognition.
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3DiVi Inc.
David Mitchell
+7 (351) 211-5099
3divi.ai
David Mitchell
+7 (351) 211-5099
3divi.ai
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