CogVisIntelligence

Real-time GPU vision: plates and faces.

In Development Computer vision

CogVisIntelligence is a modular, GPU-accelerated computer-vision stack. It reads licence plates from any angle through extreme degradation, tracks them with ghost-resistant persistent IDs, and runs reconstructable FaceID with age, gender and emotion estimation.

What it does

Everything runs locally through onnxruntime with CUDA. No frame leaves the site, which is usually the deciding constraint for the environments that need this.

Closed source. Deployed under written agreement, with the privacy and retention terms set per site.

Who it is for

Operators of sites that need plate or face recognition on their own hardware rather than in a vendor cloud.

What it costs

Licensed per deployment.

How we price everything else →

Terminology

Words this page uses in a specific sense.

Ghost-resistant tracking
Identity tracking that avoids creating a spurious new track ID when an object is briefly occluded or re-enters the frame.
ONNX Runtime
A cross-platform inference engine that runs models exported to the open ONNX format, here with the CUDA execution provider for GPU acceleration.

Facts

FieldValue
NameCogVisIntelligence
StatusIn Development
CategoryComputer vision
PlatformsWindows, Linux
PricingLicensed per deployment.
SourceClosed source
PublisherCognitive Industries
Published fromBrisbane, Queensland, Australia

Capabilities behind it

Computer vision

Real-time GPU pipelines: licence plates through extreme degradation, FaceID with persistent tracking, fire and smoke detection.

Sources

Where this page states a standard, an obligation or a research result, this is what it is drawn from. All external, all checkable.

  1. ONNX Runtime — the inference engine behind the vision stack
  2. Keystroke dynamics research overview — Computers & Security — the basis for HumanIO timing models
  3. Fitts, P. M. (1954), The information capacity of the human motor system — the motor-control law behind cursor submovements

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Last reviewed · Site changelog