Visitor tracking system for retail store analytics
The business goal
The goal of this project was to build a retail analytics system. Within the framework of the current project, the following tasks were considered:
1) definition of characteristics of the general traffic of visitors including volume and time of entrance / exit of visitors in the area of the trading hall;
2) determination of personal characteristics of visitors: maximum / minimum and average length of stay on the trading floor;
3) determination of the individual characteristics of visitors: the identification of regular customers (using unique features, for example, a person) and their preferences (client traffic maps through the trading floor area).
From the technical point of view we used two video cameras installed inside the store, the view angle of which allows you to monitor the input / output zones, and the resolution is sufficient for personal identification (Full HD, or higher) and a server equipped with a GeForce GTX 1080, the performance of which allows to process the video stream in real time. We used Ubuntu as main OS and Python with such frameworks like Caffe, Pytorch, Numpy, Sklearn, Scipy and OpenCV.
All information about visitors generated during processing is stored in the specified formats (.mp4, .csv, .txt); the values of the main parameters, the input and output paths can be configured using the console user interface.
As a result of the project, our customer received a better understanding of marketing and boosted its revenues by 16%. He also plans to enhance this solution for the whole network of stores.