In this paper we present a real-time dance visualization framework with the goal of easily mapping motion data from an accelerometer and a gyroscope into visual effects that users can compose and appropriate to their own dancing style. We used this framework to design a set of dance-tovisuals mappings through a user-centered approach. As a result, we conclude with a list of factors that help users to understand how to interact with a real-time dance visualization with no prior instructions.

We present Canvas Dance, a prototype of an interactive dance visualization for large-group interaction that targets non-professional dancers in informal environments such as parties or nightclubs, and uses the smartphones of the dancers as the input device for the motion signal. The visualization is composed of individual representations for each dancer, and the visual mappings designed for their dance moves have three main goals: to help the users identify their own representation, to uncover and inspire imitation among dancers, and to support unpredictable dance moves.

Interactivity is a unique forum of the ACM CHI Conference that showcases hands-on demonstrations, novel interactive technologies, and artistic installations. At CHI 2015 in Seoul we hosted more than 30 exhibits, including an invited digital interactive art exhibit. Interactivity highlights the diverse group of computer scientists, sociologists, designers, psychologists, artists, and many more who make up the CHI community.

In this work in progress we present early results in the process of understanding how interactive dance visualizations can inspire coordinated dance moves between dancers in informal contexts. Inspired by observations at nightclubs and parties with DJs, we designed an interactive dance visualization prototype called "Canvas Dance" and evaluated it in a user study with 3 small groups of people. We conclude by offering a set of design considerations for future work on interactive dance visualizations for non-professional dancers in informal contexts.