Abstract
The aim of this paper is to present an integrated system consisted of a RGB-D camera and a software able to monitor shoppers in intelligent retail environments. We propose an innovative low cost smart system that can understand the shoppers’ behavior and, in particular, their interactions with the products in the shelves, with the aim to develop an automatic RGB-D technique for video analysis. The system of cameras detects the presence of people and univocally identifies them. Through the depth frames, the system detects the interactions of the shoppers with the products on the shelf and determines if a product is picked up or if the product is taken and then put back and finally, if there is not contact with the products. The system is low cost and easy to install, and experimental results demonstrated that its performances are satisfactory also in real environments.
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Liciotti, D., Contigiani, M., Frontoni, E., Mancini, A., Zingaretti, P., Placidi, V. (2014). Shopper Analytics: A Customer Activity Recognition System Using a Distributed RGB-D Camera Network. In: Distante, C., Battiato, S., Cavallaro, A. (eds) Video Analytics for Audience Measurement. VAAM 2014. Lecture Notes in Computer Science(), vol 8811. Springer, Cham. https://doi.org/10.1007/978-3-319-12811-5_11
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DOI: https://doi.org/10.1007/978-3-319-12811-5_11
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