PMGS: Reconstruction of Projectile Motion across Large Spatiotemporal Spans via 3D Gaussian Splatting

• URL: http://arxiv.org/abs/2508.02660v1
• Date: Mon, 04 Aug 2025 17:49:37 GMT
• Title: PMGS: Reconstruction of Projectile Motion across Large Spatiotemporal Spans via 3D Gaussian Splatting
• Authors: Yijun Xu, Jingrui Zhang, Yuhan Chen, Dingwen Wang, Lei Yu, Chu He,
• Abstract summary: This study proposes PMGS, focusing on reconstructing Projectile via 3D Gaussian Splatting.<n>We introduce an acceleration constraint to bridge Newtonian mechanics and pose estimation, and design a dynamic simulated deformation strategy that adaptively schedules learning rates based on motion states.
• Score: 9.314869696272297
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for physical consistency. This study proposes PMGS, focusing on reconstructing Projectile Motion via 3D Gaussian Splatting. The workflow comprises two stages: 1) Target Modeling: achieving object-centralized reconstruction through dynamic scene decomposition and an improved point density control; 2) Motion Recovery: restoring full motion sequences by learning per-frame SE(3) poses. We introduce an acceleration consistency constraint to bridge Newtonian mechanics and pose estimation, and design a dynamic simulated annealing strategy that adaptively schedules learning rates based on motion states. Futhermore, we devise a Kalman fusion scheme to optimize error accumulation from multi-source observations to mitigate disturbances. Experiments show PMGS's superior performance in reconstructing high-speed nonlinear rigid motion compared to mainstream dynamic methods.

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