Warped motion prediction beyond AV1

Mohammed Golam Sarwer; Rachel Barker; Jianle Chen; Debargha Mukherjee

doi:10.1117/12.2680783

4 October 2023 Warped motion prediction beyond AV1

Mohammed Golam Sarwer, Rachel Barker, Jianle Chen, Debargha Mukherjee

Proceedings Volume 12674, Applications of Digital Image Processing XLVI; 126740M (2023) https://doi.org/10.1117/12.2680783
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

In AV1 local warped motion mode, the warped motion parameters of the current block are derived by fitting a model to nearby motion vectors using least-squares. This paper extend this mechanism to add two new warped motion modes ( called WARP_EXTEND and WARP_DELTA), which provide different ways to compute a local warped motion model. In the proposed WARP_EXTEND mode, a warped motion model is constructed by smoothly extending the motion of neighboring blocks into the current block, with modification based on the signaled motion vector. In the proposed WARP_DELTA mode, at first, the parameters of the warped motion model of the current coding block is predicted from the previously encoded/decoded blocks. Then the difference between the current block model parameters and the predicted model parameters are signaled. For each block, a warped motion reference list ( WRL) is maintained to store all of the predicted model parameters. The WRL is generated from the corner motion vectors (MVs) and from the warped motion model of the spatial neighboring blocks. A model parameter bank is also maintained to store the model parameters of the previously decoded blocks of the current frame. If there are not enough candidates from the spatial neighborhood to fill the WRL, the warped motion models from the model parameter bank are inserted to the WRL. Besides WARP_EXTEND and WARP_DELTA modes, this paper also proposes a separate single reference prediction mode where motion vector (MV) of the current block is predicted from the WRL. The simulation results show -1.18% (YUV) and -1.53%(YUV) compression gain as compared to the existing AV1 warped motion in random access and low delay configurations, respectively.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mohammed Golam Sarwer, Rachel Barker, Jianle Chen, and Debargha Mukherjee "Warped motion prediction beyond AV1", Proc. SPIE 12674, Applications of Digital Image Processing XLVI, 126740M (4 October 2023); https://doi.org/10.1117/12.2680783

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