In this paper, we present a novel framework for global non-rigid registration of multi-view scans captured using consumer-level depth cameras. In our method, all scans from different viewpoints are allowed to undergo large non-rigid deformations and finally fused into a complete high quality model. To avoid the well-known loop closure problem, we simultaneously optimize a global alignment problem instead of pairwise non-rigid registration in succession. We employ a joint point-to-point and point-to-plane positional constraint to reduce the influence of wrong correspondences, and incorporate an as-conformal-as-possible constraint to avoid mesh distortions during deformation. We also design a reweighting scheme on position and transformation to reduce registration errors. Experimental results on both public datasets and real scanned datasets demonstrate that our approach outperforms state-of-the-art methods through extensive quantitative and qualitative evaluations.
Wu et al. REF introduced an as-conformal-as-possible energy to avoid mesh distortion.
Global as-Conformal-as-Possible Non-Rigid Registration of Multi-view Scans
2019 IEEE International Conference on Multimedia and Expo (ICME)
2019 IEEE International Conference on Multimedia and Expo (ICME)
Computer Science