Abstract
Negotiations and casual exchanges that involve different cultures may often lead to misunderstandings and eventually adverse outcomes. These conflicts can be easily avoided if both parties are familiarized with each other’s culture. This paper proposes a novel way of tackling this problem by using computer vision and identifying hand gestures that are particular to a culture. Such gestures, also known as emblems, are used frequently during interaction. There is a certain complexity to emblems, and their identification could provide vital information during communication if recognized accurately. An example for this case is the “thumbs up” gesture, where the thumb is extended while the other fingers are curled up. This gesture, while positive in the West, can be insulting in other countries. The implemented computer vision software was able to detect five distinct hand gestures that had one specific meaning in the United States, as well as other connotations in other countries. This helped inform participants with residency in the United States about additional meanings of familiar hand gestures that are commonly used in North America. The main purpose of culturally-sensitive technology is to help a user get acquainted with socio-cultural particularities of another group. Possible applications are discussed further, such as serving as a cultural interpreter during a diplomatic or business exchange or aiding in cultural sensibility training for tourists traveling to a new country.
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Acknowledgements
I would like to thank Roger F. Malina for his invaluable support in the development of the project, as well as the members of the ArtSciLab. Additionally, I am grateful to all the volunteers that were excited to try the software with me and gave me instrumental feedback.
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Kubli, C. (2020). Emblem Recognition: Cultural Coaching Software via Hand Gestures. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-60700-5_9
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DOI: https://doi.org/10.1007/978-3-030-60700-5_9
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