TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences

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.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i4.32453
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
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article

TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences

Seungjoon Yang, Soowoong Kim, Junho Choi, Gun Bang et al.
Proceedings of the AAAI Conference on Artificial Intelligence
Advanced Vision and Imaging
article

TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences

Seungjoon Yang, Soowoong Kim, Junho Choi, Gun Bang, Minseong Kwon
article en

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.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(4)
Electronics and Telecommunications Research Institute (KR), Ulsan National Institute of Science and Technology (KR)
Openalex Percentile: Top 73%
Advanced Vision and Imaging
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TSDF-Based Efficient Motion-Compensated Temporal Interpolation for 3D Dynamic Sequences — Seungjoon Yang, Soowoong Kim, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS