In point cloud compression, exploiting temporal redundancy for inter predictive coding is challenging because of the irregular geometry. This paper proposes an efficient block-based inter-coding scheme for color attribute compression. The scheme includes integer-precision motion estimation and an adaptive graph based in-loop filtering scheme for improved attribute prediction. The proposed block-based motion estimation scheme consists of an initial motion search that exploits geometric and color attributes, followed by a motion refinement that only minimizes color prediction error. To further improve color prediction, we propose a vertex-domain low-pass graph filtering scheme that can adaptively remove noise from predictors computed from motion estimation with different accuracy. Our experiments demonstrate significant coding gain over state-of-the-art coding methods.
@article{arxiv.2210.08262,
title = {Motion estimation and filtered prediction for dynamic point cloud attribute compression},
author = {Haoran Hong and Eduardo Pavez and Antonio Ortega and Ryosuke Watanabe and Keisuke Nonaka},
journal= {arXiv preprint arXiv:2210.08262},
year = {2022}
}