How does camera-based people counting and flow analysis work?

Published on by Omnicog team. Updated on .

Camera-based people counting uses computer vision to detect and track people in the scene and turn their movement into metrics for entries, exits, occupancy and flow. In most cases this is done without facial recognition, using aggregated data.

Beyond counting

An application can measure dwell time, queues, trajectories, heat maps and bottlenecks, helping you understand how a space is used over time.

What affects accuracy

  • Camera position and height.
  • Resolution and field of view.
  • People blocking each other.
  • Lighting and contrast.
  • Correct definition of counting zones and lines.

Privacy

In many projects, the purpose is achieved with aggregated metrics and anonymous tracking, without facial recognition and in line with Brazil’s General Data Protection Law (LGPD).

Read next: people flow with computer vision.

Assessment of your cameras

The first step is to look at the cameras you already have and tell you what they can do. Then a proof of concept with your own footage shows the result in the field. Depending on the size of the project, both steps can be free of charge, and the proof of concept starts running within 10 days of the agreement between the parties.

How the assessment works

Frequently asked questions

Is camera-based people counting accurate?

It can be highly accurate when the camera has good height, angle and lighting and the counting lines are well defined. Accuracy is measured during the pilot against a reference count.

What do you want your cameras to tell you?

Tell us what you need to detect, measure or monitor. We start with the problem, not the technology, and the assessment uses images from the cameras you already have.

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