Create a Store Traffic Monitoring Solution

Track and count people inside and outside of a facility using three different video streams.

Target Operating System Ubuntu* 16.04 LTS
Programming Language C++, Python*
Time to Complete 50 - 70 minutes

View on GitHub*

What It Does

Learn to build and run an application that:

Monitor people's activity inside and outside a facility

Recognizes when inventory on a shelf is getting low

Utilizes a trained neural network to detect objects

The counter uses the inference engine included in the OpenVINO™ toolkit. A trained neural network detects objects within a designated area by displaying a green bounding box over them. This reference implementation identifies multiple intruding objects entering the frame and identifies their class, count, and time entered.

What We Used

Hardware Requirements

5th generation Intel® Core™ processor (or newer) or Intel® Xeon® processors (v4 or v5) with Intel® Graphics Technology

USB webcam

Software Requirements

Ubuntu* 16.04 LTS

OpenVINO™ toolkit