Create a People Counter Solution

Detect people in a designated area and determine the number of people in the frame, the average time they are in the frame, and the total count. Gain important business insight using the information generated.

Target Operating System Ubuntu* 16.04 LTS
Time to Complete 30 minutes

GitHub* (C++)

What You Will Learn

Learn how to create a smart video IoT solution that records the number of people moving in and out of a camera frame. Use this solution to track shoppers, people entering a facility, and more.

Gain insight into the following solutions:

  • Computer vision applications for IoT
  • Inference to analyze datasets
  • Retail or Industrial market IoT

Use the skills learned in this reference implementation to develop similar IoT solutions.

Learn to build and run an application with these capabilities:

Detect people within a designated area by displaying a green bounding box over them.
Count people in the frame, how long they are in the frame, and the total number of people seen.
Send the data to a local web server using the Paho* MQTT C client libraries.

How It Works

The application uses a video source (such as a camera) to capture images, and then uses an inference engine to help process the data.

  1. A trained neural network detects people within a designated area by displaying a green bounding box over them.
  2. The application counts the people in the current frame, the duration that a person is in the frame (time elapsed between entering and exiting a frame), and the total number of people seen.
  3. Data is sent to a local web server using the Paho* MQTT C client libraries.