KnockGS:interaction-Grounded Calibrationof Physical Gaussian Representations

📅 2026-08-27
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
提出KnockGS方法,通过分析物体在已知力作用下的动态响应来估计3D高斯表示物体的弹性与密度参数,从而解决材料参数自动推断问题。
📝 Abstract
Physics-integrated 3D Gaussian representations now allow reconstructed deformable objects to be simulated and rendered under explicit material models. Existing pipelines, however, assume that material parameters are known or manually specified, limiting their applicability when these parameters must be inferred from observed object dynamics. We propose KnockGS, an interaction-response PhysicalGS framework that estimates the elasticity and density scales of a 3D Gaussian object from its dynamics under a known applied force. Rather than treating physical simulation only as a forward process, we turn the force-induced response into a calibration signal: temporal response features are xtracted from the observed dynamics, the two material scales are estimated from those features, and the estimate is then frozen and written back into the same simulator so that it can be tested on an interaction it was never fitted to.We evaluate the framework on both parameter recovery and response-level fidelity. The estimated scales are compared against hidden ground truth, and the re-simulated object is measured against the target using 3D particle trajectories, response-curve statistics, and rendered-frame quality. Across five held-out material targets, our method recovers the scales substantially more accurately than response retrieval, global regression, or a fixed default material, and the frozen estimate remains predictive under interactions that differ in direction and in magnitude. Interaction response therefore carries enough information to calibrate material scales in physically grounded 3D Gaussian representations.Our study is a first step toward interactive PhysicalGS systems that calibrate a Gaussian asset whose rendered appearance and simulated response are consistent.
Problem

Research questions and friction points this paper is trying to address.

3D Gaussian representations
material parameters
dynamics
elasticity
density
Innovation

Methods, ideas, or system contributions that make the work stand out.

Interaction-Response
PhysicalGS
Material Calibration
Gaussian Representations
Dynamic Simulation