A Computer Vision System for Monitoring Ice-Cream Freezers


In this paper, we describe a computer vision system aimed at monitoring the evolution of the content of a commercial ice-cream freezer. In particular, the system is able to detect the volume occupied by ice-creams in a basket and to track ice-cream sales. To this end, three modules have been developed performing the detection of the baskets and the products inside them, along with the tracking of the interactions with the freezer to take/drop products. The system comprises four cameras connected to an embedded mini-computer able to communicate with a telemetry system that sends information about the freezer context. Our proposed methods achieve promising results for the basket detection and the product tracking (accuracy around 70–80%) and good results in the volume estimation.

In International Conference on Image Analysis and Processing
Alessandro Torcinovich
Alessandro Torcinovich
Postdoc in Machine Learning

My research interests include Game Theoretic, Deep and Weakly Supervised Learning