Video Condensation by Ribbon Carving

Efficient browsing of long video sequences is a key tool in visual surveillance, e.g., for postevent video forensics, but can also be used for fast review of motion pictures and home videos. While frame skipping (fixed or adaptive) is straightforward to implement, its performance is quite limited. Although more efficient techniques have been developed, such as video summarization and video montage, they lose either the temporal or semantic context of events. A recently proposed method called video synopsis deals with some of these issues but involves multiple processing stages and is fairly complex.
Video condensation
, that we propose here, is novel in the way information is removed from the space-time video volume, is conceptually simple and relatively easy to implement. We introduce the concept of a
video ribbon
inspired by that of a seam recently proposed for image resizing. We recursively carve ribbons out by minimizing an activity-aware cost function using dynamic programming. The ribbon model we develop is flexible and permits an easy adjustment of the compromise between temporal condensation ratio and anachronism of events. We also propose sliding-window ribbon carving to handle streaming video and demonstrate the method's efficiency on motor and pedestrian traffic data.