Exploiting Temporal Redundancy of Visual Structures for Video Compression

Summary form only given. We present a video coding system that partitions the scene into "visual structures" and a residual "background" layer. The system exploits the temporal redundancy of visual structures to compress video sequences. We construct a dictionary of track-templates, which correspond to a representation of visual structures. We subsequently choose a subset of the dictionary's elements to encode video frames using a Markov Random Field (MRF) formulation that places the track-templates in "depth" layers. Our video coding system offers an improvement over H.265/H.264 and other methods in a rate-distortion comparison.