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ARMart – AR-Based Shopping Assistant to Choose and Find Store Items

Röddiger, Tobias; Doerner, Dominik; Beigl, Michael

Abstract:
Supermarkets offer a wide range of products which makes it challenging for consumers to choose between the different options and find the items they are looking for. Augmented Reality (AR) applications, however, have a high potential to enrich real-world objects with information which can be leveraged to improve this process. We developed an application that runs on a regular smartphone and helps users to choose between packaged groceries based on factors such as calories or sugar, rated on a scale from red (bad) to green (good). Compared to previous work, there is no need for a priori knowledge about product locations making the system suitable for many use cases. Moreover, information maps precisely onto the outline of the product's and not on the approximate shelf. To do so, no modifications of the objects, such as specialized tags, are necessary. Additionally, users can find items just by entering the name. Highlighting the packaging virtually helps to find the desired product. It is also possible to make a binary distinction between groceries that contain specific ingredients.



Originalveröffentlichung
DOI: 10.1145/3267305.3267631
Scopus
Zitationen: 3
Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2018
Sprache Englisch
Identifikator ISBN: 978-1-4503-5966-5
KITopen-ID: 1000089192
Erschienen in 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018; Singapore; Singapore; 8 October 2018 through 12 October 2018
Verlag ACM Press, New York (NY)
Seiten 440–443
Nachgewiesen in Scopus
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