last update: August 9, 2006

Screaming Market

Bowbow Yang-Ting Shen, Kristy Liao, Yu-Dang Chen

[Screaming Market Video download]

[Screaming Market Demo download] (needs to work with a Webcam and Attention Meter)

Introduction

ScreamMarket is an interactive night-market show that interacts with audience? attention and feedbacks. This system demonstrated how audience engaged with the performance by monitoring their visual attention and audio feedbacks. The interactive show is implemented in Adobe Flash with Attention Meter as an attention-based triggering mechanism.

(Dang, Kristy, Jackie, Bowbow)

The Scream Market presents an animation of two Taiwanese girls if an audience is paying attention to the stage. When the crowd shows their interest and screams, the virtual girls dance and entertain them.

ScreamMarket transformed the Taiwanese traditional night market experience into a virtual and simulated space. In the beginning, an image of stage in night marketplace is blurred, but it gets clearer when the audiences pay attention to it. If more people are gathering in front of the stage, the dancers will show up. The audience can yell to respond to the stage and get visual feedback.

ScreamMarket is implemented in Flash with Attention Meter. By using a microphone, as the volume of the audience increases, the performers become more active and entertaining. The process of interaction is similar to the behavior that we watch the interactive show or bargain with the hawker in the night market. According to the method of interaction, the users are not simply viewers, but also performers in their own right. 30 people took turns in an exhibition interacting with the ScreamMarket. People were able to figure out and use it within a minute. It constrains output based on the regular environment noise, so that people may need to scream very loudly to interact with the Flash movie. The atmosphere of the interaction creates a realistic simulation of the night market.

Publication

Lee, C.H., Wetzel, J., Jang, C.Y., Shen, Y.T., Chen, T.H., Selker, T. Attention Meter: A Vision-based Input Toolkit for Interaction Designers. Work-in-progress in CHI 2006. (Full-text PDF)