A comparative study of representations for folk dances recognition in video
Dance traditions constitute a significant aspect of cultural heritage around the world. The organization, semantic analysis, and retrieval of dance-related multimedia content (i.e., music, video) in databases is, therefore, crucial to their preservation. In this paper we explore the problem of folk dances recognition from video recordings, focusing on Greek folk dances, using different representations for the data. To this end we have employed the well-known Bag of Words model, in combination with dense trajectories, as well as with streaklines descriptors. Furthermore, we have adopted a representation based on Linear Dynamic Systems, including a novel variant that uses dense trajectories descriptors instead of pixel intensities. The performance of the aforementioned representations is evaluated and compared, in a classification scenario involving 13 different dance classes.