1 research outputs found
Towards in-store multi-person tracking using head detection and track heatmaps
Computer vision algorithms are being implemented across a breadth of
industries to enable technological innovations. In this paper, we study the
problem of computer vision based customer tracking in retail industry. To this
end, we introduce a dataset collected from a camera in an office environment
where participants mimic various behaviors of customers in a supermarket. In
addition, we describe an illustrative example of the use of this dataset for
tracking participants based on a head tracking model in an effort to minimize
errors due to occlusion. Furthermore, we propose a model for recognizing
customers and staff based on their movement patterns. The model is evaluated
using a real-world dataset collected in a supermarket over a 24-hour period
that achieves 98% accuracy during training and 93% accuracy during evaluation