Will Existing Cameras Work for Computer Vision?
Existing cameras may suit computer vision if they provide the required angle, distinguishable features and accessible video. Suitability is task-specific. A camera showing area occupancy may need different settings to inspect a small part.
Start with what must be visible
Queues need visible boundaries and distinguishable people. Gloves need a sufficiently large hand image; displays need legible digits. Equal camera resolution does not mean equal suitability for every scenario.
At Busted, we compare the required feature with original footage, first under ordinary conditions and then in difficult clips. This establishes whether the current camera position is enough or the angle should change.
Check motion and lighting
Fast hands and products may blur. Glare and strong lighting contrasts obscure detail. Placement, light, compression and image settings affect analytics quality. Axis's video-quality guide also describes these factors.
Compare day and evening shifts. A single good frame does not show performance under different loads or lighting.
Establish the connection method
Deployment requires a working way to retrieve streams or recordings. App access should be supplemented with camera model, recorder and interface details. Test reconnection after outages too.
For compatible devices, ONVIF Profile T describes H.264/H.265 video streaming and related data exchange. Confirm the required interface for the actual device and client.
The initial assessment
Prepare model lists, camera positions and original clips of the target operation. For each scenario, note visibility, difficult conditions and data access. Then identify where existing installation works and where changes are needed.
Busted helps begin with an assessment of existing cameras. The output is a list of observable tasks and specific imaging and connectivity requirements.