Name
Abstract | ||
|---|---|---|
In this paper we introduce a video post-processing method that enhances the rhythm of a dancing performance, in the sense that the dancing movements are more in time to the beat of the music. The dancing performance as observed in a video is analyzed and segmented into motion intervals delimited by motion beats. We present an image-space method to extract the motion beats of a video by detecting frames at which there is a significant change in direction or motion stops. The motion beats are then synchronized with the music beats such that as many beats as possible are matched with as little as possible time-warping distortion to the video. We show two applications for this cross-media synchronization: one where a given dance performance is enhanced to be better synchronized with its original music, and one where a given dance video is automatically adapted to be synchronized with different music. |
Year | Venue | Keywords |
|---|---|---|
2018 | Computational Visual Media | video processing, synchronization, motion segmentation, video analysis |
Field | DocType | Volume |
Computer vision,Synchronization,Video processing,Dance,Synchronizing,Beat (music),Artificial intelligence,Rhythm,Distortion,Mathematics | Journal | 4 |
Issue | Citations | PageRank |
3 | 1 | 0.35 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rachele Bellini | 1 | 6 | 0.78 |
| Yanir Kleiman | 2 | 228 | 8.06 |
| Daniel Cohen-Or | 3 | 10588 | 533.55 |