AI & ML
Real-Time Self-Penetration Repair for Skinned Characters with Soft Contact Budgets
arXiv cs.GR0 views
arXiv:2611.09693v1 Announce Type: new Abstract: Motion that is plausible on one body can penetrate another after a change in shape, and motion models can produce self-penetration on their native characters. We present a training-free post-process that reduces these artifacts through pose correction followed by bounded skin compression. The module attaches to any motion model whose native character and output character have compatible character packs, without access to model internals. Each pack is built offline from the rig and skin without training. A vertex-level pose layer solves a local quadratic program in plain C on one CPU core, and a stateless contact deformer acts on the host's final skinned mesh. A part-dependent soft-tissue budget allocates correction between pose and skin through a static convention. Source penetration contributes no extra allowance; optional cloth thickness and compliance modify the pose layer's collision surface. Operation is causal or uses a short buffered lookahead, with frame-exact pass-through at the native interface for clean, inactive frames in the zero state. Across 320 unseen clips and 3 body shapes, the fraction of frames with hand-torso depth above 20 mm falls from 15.53% for copied motion to 0.00%, with final maximum depth 9.3 mm over every frame. Mean pose and skin costs are 1.11 and 1.18 ms, respectively, and their sum of 2.29 ms is a sub-frame processing cost. The median joint-velocity high-frequency ratio relative to copied target motion is 1.008.
Source:https://arxiv.org/abs/2611.09693PreviousAudiovisual Disparities in VR: Impact on Spatial PerceptionNextFrom Geometry to Function: A Multi-Task LiDAR Benchmark Dataset for Semantic and Functional Parsing of Urban Facades
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