3D Reconstruction of Deformable Revolving Object under Heavy Hand Interaction
This addresses the problem of reconstructing deformable objects under occlusion for applications like digital pottery, though it appears incremental as it builds on existing optimization and symmetry concepts.
The paper tackles 3D reconstruction of deformable objects during live pottery making, where heavy hand interaction and deformation challenge classical techniques, achieving a 7.60mm average reconstruction error that significantly outperforms state-of-the-art methods.
We reconstruct 3D deformable object through time, in the context of a live pottery making process where the crafter molds the object. Because the object suffers from heavy hand interaction, and is being deformed, classical techniques cannot be applied. We use particle energy optimization to estimate the object profile and benefit of the object radial symmetry to increase the robustness of the reconstruction to both occlusion and noise. Our method works with an unconstrained scalable setup with one or more depth sensors. We evaluate on our database (released upon publication) on a per-frame and temporal basis and shows it significantly outperforms state-of-the-art achieving 7.60mm average object reconstruction error. Further ablation studies demonstrate the effectiveness of our method.