Virtual Line Calibration
Place the line where the camera view provides a clear crossing path and sufficient object scale.
BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformBAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformUse tracked movement across a calibrated virtual line to create directional operational events.
How it works
Each stage remains observable and can be validated independently.
Place the line where the camera view provides a clear crossing path and sufficient object scale.
The within-camera track supplies movement history so the policy can distinguish permitted and relevant directions.
Use crossings for entry and exit counts, directional flow or restricted-boundary events according to the configured workflow.
Capability, compatibility and performance depend on the camera scene, approved models, infrastructure and acceptance criteria. Human review remains appropriate for critical decisions.
Related guidance
Frequently asked questions
Yes. When tracking and scene calibration support it, a policy can evaluate the direction of a crossing.
Yes. BAV ONE supports assessed edge, on-premises, cloud and hybrid architectures. The selected design depends on camera access, compute, bandwidth, data-control and operational requirements.
No. Compatibility depends on stream access, protocol, resolution, frame rate, camera angle, lighting, network conditions and the selected use case. Bharat AI Vision validates these factors before rollout.
Begin with a camera and workflow assessment, then validate a focused one-to-four-camera pilot against agreed operating conditions and acceptance criteria.
Validate before rollout
Map the operating requirement, assess compatible streams and validate a focused workflow before expanding.