Fast Video Retargeting Based on Seam Carving with Parental Labeling
This work addresses video retargeting for multimedia applications, but it is incremental as it builds on existing seam carving techniques.
The paper tackled the problem of slow processing and frame-wise discontinuities in video retargeting using seam carving, resulting in a 93% reduction in processing time and improved frame-wise consistency.
Seam carving is a state-of-the-art content-aware image resizing technique that effectively preserves the salient areas of an image. However, when applied to video retargeting, not only is it time intensive, but it also creates highly visible frame-wise discontinuities. In this paper, we propose a novel video retargeting method based on seam carving. First, for a single frame, we locate and remove several seams instead of one seam at once. Second, we use a dynamic spatiotemporal buffer of energy maps and a standard deviation operator to carve out the same seams in a temporal cube of frames with low variation in energy. Last but not least, an improved energy function that considers motions detected through difference method is employed. During testing, these enhancements result in a 93 percent reduction in processing time and a higher frame-wise consistency, thus showing superior performance compared to existing video retargeting methods.