Love in Action: Gamifying Public Video Cameras for Fostering Social Relationships in Real World
Zhang Zhang, Da Li, Geng Wu, Yaoning Li, Xiaobing Sun, Liang Wang
TL;DR
An AI-enhanced video analysis system is built incorporating multiple visual analysis modules like person detection, attribute recognition, and action recognition, to assess the performer's body language quality and shows significant improvements in their social friendships.
Abstract
In this paper, we create "Love in Action" (LIA), a body language-based social game utilizing video cameras installed in public spaces to enhance social relationships in real-world. In the game, participants assume dual roles, i.e., requesters, who issue social requests, and performers, who respond social requests through performing specified body languages. To mediate the communication between participants, we build an AI-enhanced video analysis system incorporating multiple visual analysis modules like person detection, attribute recognition, and action recognition, to assess the performer's body language quality. A two-week field study involving 27 participants shows significant improvements in their social friendships, as indicated by self-reported questionnaires. Moreover, user experiences are investigated to highlight the potential of public video cameras as a novel communication medium for socializing in public spaces.