Leveraging Cuboids for Better Motion Modeling in High Efficiency Video Coding

In conventional video compression systems, motion model is used to approximate the geometry of moving object boundaries. It is possible to relieve motion model from describing discontinuities in the underlying motion field, by incorporating motion hint that can predict the spatial structure of future frames using the structure of reference frames. However, formation of highly accurate motion hint is computationally demanding, in particular for high resolution video sequences. Cuboids, rectangular regions derived using statistical features, attempt to separate out different objects present in the scene; they are computationally efficient and have sparse representation. Leveraging on the advantages of cuboids, in this paper, we propose to discover homogeneous motion regions and their associated motion based on cuboids. Afterwards, the estimated motion models and their domains are applied to form a prediction of the current frame. Experimental results show that a savings in bit rate of 3.96% is achievable over standalone HEVC reference, if this predicted frame is used as an additional reference frame for the current frame.