On the occasion of the 21st IEEE “Conference on Business Informatics “, 2019. Early Stage Researcher Daniel Mora presented the paper “How Computer Vision Provides Physical Retail with a Better View on Customers” as representative of the August-Wilhelm Scheer Institute for digitized Products and Processes (AWSi) and PERFORM. In the course of the annual business informatics conference in mid-July, he traveled to the National Research University Higher School of Economics, Moscow, Russia; where discussed current developments and trends with an international audience of experts, e.g., in the areas of artificial intelligence and omnichannel retail.
The work presented there focuses on the main research topics of the “VICAR” project. On this paper, Daniel Mora, Dr. Oliver Nalbach and Dr. Dirk Werth, investigate how to leverage recent technologies from the field of Computer Vision as a data acquisition method in physical retail to design a system that can lead store owners and retail managers to improve their customers’ shopping experience, and use brick and mortar stores more satisfactorily and at the same time address their business needs.
Physical retailers have to transform into the digital world. The main requirement for Physical retailers in order to transform is to have suitable data acquisition methods, as well, as resulting applications that are viable in an offline setting. For this reason, the AWSi researchers proposed a real-time visual tracking system which can provide movement paths of customers in a store and also semantically enriched tracks of visited locations (E.g., shelves, product categories, or departments), to then create a number of (real-time) applications like in-store recommender systems, management dashboards, and shoplifting prevention.
The VICAR project is partly funded by the German ministry of education and research (BMBF), reference number 01S17085C.
ESR Daniel Mora is a part of the European Training Network project PERFORM that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement No 765395.