Nonlinear editing by Generative Video

Nonlinear video editors manipulate video sequences by contents irrespective of frame order. These are computer based tools that contrast with analogue linear tape editing technologies. The latter are extremely taxing of videographers time and resources. Current computerized editing methods represent video in terms of individual images. This poses a formidable task to the manipulation task due to the large data volumes associated with them. We discuss a framework-Generative Video, which deals with this problem in an efficient way. Generative Video represents video sequences in terms of constructs-compact models. These are world images and generative operators. World images are augmented images, which contain the non-redundant information in the video sequence, and they describe video contents information. For each independently moving object we have a different world image. World images are stratified in layers according to occlusion information. The generative operators access video contents information, such as the shape and motion of objects moving in the sequence. Nonlinear video editing is realized by applying generative operators to world images. This approach to nonlinear editing facilitates the access, storage, and manipulation of video contents information. We describe the main properties of Generative Video and demonstrate nonlinear editing on a real video sequence.