TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences
Soowoong Kim, Minseong Kwon, Junho Choi, Gun Bang, Seungjoon Yang
Abstract
This paper introduces a method for efficiently interpolating 3D dynamic sequences using truncated signed distance function (TSDF) volumes. The method calculates bi-directional motions between TSDF volumes of two frames and refines them to reconstruct intermediate frames. Unlike point cloud-based methods, which can suffer from varying and irregular point densities, the uniform and dense grid structure of TSDF offers a consistent framework for estimating the true motion of objects within a scene. In our experiments, the TSDF-based method offers more precise and reliable smooth motion prediction compared to the often error-prone surface depiction in point clouds. Experimental results demonstrate improved accuracy and reduced computational complexity, making it suitable for real-time applications.
BibTeX
@article{Kim_Kwon_Choi_Bang_Yang_2025, title={TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/32453}, DOI={10.1609/aaai.v39i4.32453}, abstractNote={This paper introduces a method for efficiently interpolating 3D dynamic sequences using truncated signed distance function (TSDF) volumes. The method calculates bi-directional motions between TSDF volumes of two frames and refines them to reconstruct intermediate frames. Unlike point cloud-based methods, which can suffer from varying and irregular point densities, the uniform and dense grid structure of TSDF offers a consistent framework for estimating the true motion of objects within a scene. In our experiments, the TSDF-based method offers more precise and reliable smooth motion prediction compared to the often error-prone surface depiction in point clouds. Experimental results demonstrate improved accuracy and reduced computational complexity, making it suitable for real-time applications.}, number={4}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Kim, Soowoong and Kwon, Minseong and Choi, Junho and Bang, Gun and Yang, Seungjoon}, year={2025}, month={Apr.}, pages={4311-4319} }