ICAT-EGVE2020 - Posters and Demos

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An Automated Virtual Receptionist for Recognizing Visitors and Assuring Mask Wearing
(The Eurographics Association, 2020) Zehtabian, Sharare; Khodadadeh, Siavash; Kim, Kangsoo; Bruder, Gerd; Welch, Greg; Bölöni, Ladislau; Turgut, Damla; Kulik, Alexander and Sra, Misha and Kim, Kangsoo and Seo, Byung-Kuk
Intelligent virtual agents have many societal uses, specifically in situations in which the presence of real humans would be prohibitive. In particular, virtual receptionists can perform a variety of tasks associated with visitor and employee safety, e.g., during the COVID-19 pandemic. In this poster, we present our prototype of a virtual receptionist that employs computer vision and meta-learning techniques to identify and interact with a visitor in a manner similar to that of a real human receptionist. Specifically we employ a meta-learning-based classifier to learn the visitors' faces from the minimal data collected during a first visit, such that the receptionist can recognize the same visitor during follow-up visits. The system also makes use of deep neural network-based computer vision techniques to recognize whether the visitor is wearing a face mask or not.