A people counter is a solution that counts (or measures) the number of people who enter a designated area. You may be familiar with people counting systems, found in small shops, libraries and convenience stores, that use infrared sensors to detect people. When an infrared beam is cut (a person intercepts it by entering or exiting a door for example) the system increments a count. This technology has limitations when it comes to instances of occlusion (when person A blocks person B and person B doesn't get counted). An appropriately designed computer vision-based people counting system can be more robust in handling cases of occlusion which results in a more reliable counting system. Here we utilize the OpenCV libraries and apply the Histograms of Oriented Gradients (HOG) algorithm to create a computer vision application for people detection and counting.
What you’ll learn
- How to build a people counting computer vision application from source code in the Arduino Create IDE
- How to run the application from the command prompt on the Ubuntu desktop