Developing a Hand Gesture Recognition System for Mapping Symbolic Hand Gestures to Analogous Emojis in Computer-Mediated Communication Academic Article uri icon

abstract

  • Recent trends in computer-mediated communication (CMC) have not only led to expanded instant messaging through the use of images and videos but have also expanded traditional text messaging with richer content in the form of visual communication markers (VCMs) such as emoticons, emojis, and stickers. VCMs could prevent a potential loss of subtle emotional conversation in CMC, which is delivered by nonverbal cues that convey affective and emotional information. However, as the number of VCMs grows in the selection set, the problem of VCM entry needs to be addressed. Furthermore, conventional means of accessing VCMs continue to rely on input entry methods that are not directly and intimately tied to expressive nonverbal cues. In this work, we aim to address this issue by facilitating the use of an alternative form of VCM entry: hand gestures. To that end, we propose a user-defined hand gesture set that is highly representative of a number of VCMs and a two-stage hand gesture recognition system (trajectory-based, shape-based) that can identify these user-defined hand gestures with an accuracy of 82%. By developing such a system, we aim to allow people using low-bandwidth forms of CMCs to still enjoy their convenient and discreet properties while also allowing them to experience more of the intimacy and expressiveness of higher-bandwidth online communication.

published proceedings

  • ACM Transactions on Interactive Intelligent Systems

author list (cited authors)

  • Koh, J. I., Cherian, J., Taele, P., & Hammond, T.

citation count

  • 8

complete list of authors

  • Koh, Jung In||Cherian, Josh||Taele, Paul||Hammond, Tracy

publication date

  • March 2019