Visual Background Recommendation for Dance Performances Using Dancer-Shared Images

Abstract

Dance performances use body gestures as a language to express emotion, and lighting and background images on the stage to create the scene and atmosphere. In conventional dance performances, the background images are usually selected or designed by professional stage designers according to the theme and the style of the dance. In new media dance performances, the stage effects are usually generated by media editing software. Selecting or producing a dance background is quite troublesome, and is generally carried out by skilled technicians. The goal of the research reported in this paper is to ease this process, meaning dancers can set background images for their dance performances without the need for stage designers. Instead of searching for background images from the sea of available resources, dancers are recommended images they are more likely to use. This paper proposes the idea of a novel system to recommend images based on content-based social computing. A model to predict a dancer's interests in candidate images through social platforms, e.g., Pinterest, is proposed. With the help of such a system, dancers can select from the recommended images and set them as the backgrounds of their dance performances through a media editor. To the best of our knowledge, this would be the first dance background recommendation system for dance performances.