Exploring frame-based gesture design for immersive VR shopping environments

Bibliographic Data

ID21452809
AuthorsHuiyue Wu (0000-0001-7027-518X, Sun Yat-sen University, corresponding author), Shengqian Fu (Sun Yat-sen University), Liuqingqing Yang (0000-0003-0719-0751, Sun Yat-sen University), Xiaolong Zhang (0000-0002-0417-0002, Pennsylvania State University)
Year2022
Volume41
Issue1
Pages96-117
Publication date2022-01-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueBehaviour and Information Technology (JOURNAL)
Journal identifiersISSN: 0144-929X • E-ISSN: 1362-3001
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/0144929x.2020.1795261
OpenAlexW3042810110
LanguageEN
Citations received3
References cited61

In the design of gesture-based user interfaces, traditional gesture elicitation studies suffer from the legacy bias problem. In this paper, we conducted an exploratory study about the practical effects of frame-based design for gestural interaction with immersive VR shopping applications. In this study, we derived gestures via the traditional guessability and the framed guessability approaches. Experimental results indicated that priming participants with a frame, or a scenario, could significantly reduce the impact of legacy bias, and result in superior gesture vocabulary. However, no evidence was found that the priming technique would generate more gesture types, which may lead to lower agreement scores due to the reduction of legacy bias. Based on our findings, we propose some concrete design guidelines for gesture-based interaction. We highlight the implications of this work for the design of all gesture-based applications

Exploratory research · Frame (networking) · Gesture · Gesture recognition · Human–computer interaction · Linguistics · Multimedia · Priming (agriculture) · User experience design · Vocabulary · Artificial Intelligence · Computer Science · Hand Gesture Recognition Systems · Interactive and Immersive Displays · Tactile and Sensory Interactions

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