Recognition of social dancing from auditory and visual information
We discuss the recognition of social dancing from a real image sequence and an acoustic signal of music. Since social dancing involves somewhat complicated movements by multiple humans, it is difficult to recover a detailed description of each dancer's posture by the conventional approach based on matching of an articulated human body model to each frame of an image sequence. Using the results of the recognition process for annotating a video of social dancing, we focus on the bare minimum of motion description. We show that the motion description can be acquired from a real image sequence and an acoustic signal by simple familiar techniques of computer vision and music information processing.