Note: the following paragraph is the abstract of the research paper published on the 2017 Pioneer Research Journal. For more information, please refer to the paper.
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.