Scanning and Reconstruction for Dynamic Surfaces

We present a novel 3D scanning system with the potential for interactive acquisition and visualization of dynamic scenes. Our system uses a spatiotemporally adaptive sampling strategy, and can take advantage of multiple simultaneous scanning devices operating at different resolutions. We also employ a level set framework for reconstructing potentially dynamic scenes from multiple concurrent streams of range data. In our framework, implicit surfaces are reconstructed periodically from new samples on a coarse grid, creating a sequence of reconstructions from disjoint sample sets that is used to estimate motion in the scene. A high-resolution reconstruction proceeds alongside, where the surface is evolved by a convective flow that guides it towards the sample set. We employ a spatially-varying distance metric based on our motion estimate that adaptively controls the contribution of older samples to the final reconstruction.